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江南大学的丁锋及合作者靠大量中低水平论文和自引获得荣耀

　　作者：杜克林

　　1、前言

　　11月6日，我收到Springer发来的电子邮件，推荐阅读Circuits, Systems, 
and Signal Processing期刊的三篇最近出版的高引用率论文。自从2009年以来，
我一直是该期刊的编委/副编辑(Associate Editor)，我想研究一下这三篇论文。

　　这三篇论文是：

　　1. Ling Xu, Feng Ding. Iterative Parameter Estimation for Signal 
Models Based on Measured Data. Circuits, Systems, and Signal 
Processing, July 2018, Volume 37, Issue 7, pp 3046–3069
 	
　　2. Jiling Ding, Recursive and Iterative Least Squares Parameter 
Estimation Algorithms for Multiple-Input–Output-Error Systems with 
Autoregressive Noise. Circuits, Systems, and Signal Processing, May 2018,
 Volume 37, Issue 5, pp 1884–1906. 
 	
　　3. Junhong Li, Wei Xing Zheng, Juping Gu, Liang Hua. A Recursive 
Identification Algorithm for Wiener Nonlinear Systems with Linear 
State-Space Subsystem. Circuits, Systems, and Signal Processing, June 
2018, Volume 37, Issue 6, pp 2374–2393. 

　　首先，这三篇论文的题目都是非常相似的，都是关于参数估计和辨识的。这
些论文从标题就看得出是传统的课题，看似解决了什么问题，又好像什么也没解
决。信号处理领域研究方向和热点非常多，为什么这三篇论文成为高引用论文，
我决定挖一挖。我将把调查结果向Circuits, Systems, and Signal Processing期
刊的编委会汇报。

　　2、第一篇论文的引用和被引用分析

　　第一篇作者Ling Xu, Feng Ding来自于江南大学物联网学院。Ling Xu还属
于无锡商业职业技术学院物联网技术学院。

　　First Online: 11 November 2017
　　348 Downloads, 52 Citations
　　58 References

　　（一） 参考文献（References）分析

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　　在该文的58篇参考文献中，有20篇论文（[6，9-12，18，30，31， 40-42
，49-57]）是作者自己（Ling Xu, Feng Ding）的论文。另有2篇（26，28）他
们的有关联的合作者 Wen Xing Zheng论文。

　　可见作者的自引率是相当高的。

　　（二） 引用（Citations）分析。

　　引用该文的文献如下：

　　1. Jing Yan, Xuyang Tian, Xiaoyuan Luo and Xinping Guan. Design of 
an Embedded Communication System for Underwater Asynchronous 
Localization. IEEE Embedded Systems Letters, 2019, Volume 11, Number 
3, Page 97. [0 CITATIONS]

　　2. Xiao Zhang, Feng Ding, Ling Xu, Ahmed Alsaedi and Tasawar 
Hayat. A Hierarchical Approach for Joint Parameter and State Estimation
 of a Bilinear System with Autoregressive Noise,  Mathematics, 2019, 
Volume 7, Number 4, Page 356. [11 CITATIONS] 

　　3. Ping Ma, Feng Ding and Tasawar Hayat. Multi-innovation gradient 
estimation algorithms for multivariate equation-error autoregressive 
moving average systems based on the filtering technique, IET Control 
Theory & Applications, 2019, Volume 13, Number 13, Page 2086. [0 CITATIONS]

　　4. Huafeng Xia, Yan Ji, Yanjun Liu and Ling Xu. Maximum 
Likelihood-based Multi-innovation Stochastic Gradient Method for 
Multivariable Systems, International Journal of Control, Automation and 
Systems, 2019, Volume 17, Number 3, Page 565. [1 CITATIONS]

　　5. Xuehai Wang and Feng Ding. The filtering based parameter 
identification for bilinear-in-parameter systems,  Journal of the Franklin 
Institute, 2019, Volume 356, Number 1, Page 514. [1 CITATIONS]

　　6. Jing Chen, Feng Ding, Quanmin Zhu and Yanjun Liu. Maximum 
likelihood based identification methods for rational models,  
International Journal of Systems Science, 2019, Volume 50, Number 14, 
Page 2579. [0 CITATIONS]

　　7. Xiao Zhang, Feng Ding, Ling Xu and Erfu Yang. Highly 
computationally efficient state filter based on the delta operator. 
International Journal of Adaptive Control and Signal Processing, 2019, 
Volume 33, Number 6, Page 875. [15 CITATIONS]

　　8. Feng Ding, Jian Pan, Ahmed Alsaedi and Tasawar Hayat, 
Gradient-Based Iterative Parameter Estimation Algorithms for Dynamical
 Systems from Observation Data. Mathematics, 2019, Volume 7, Number 
5, Page 428. [11 CITATIONS]

　　9. Huan Xu, Feng Ding and Erfu Yang. Recursive search-based 
identification algorithms for the exponential autoregressive time series 
model with coloured noise.  IET Control Theory & Applications, 2019, 
DOI: 10.1049/iet-cta.2019.0429 [0 CITATIONS]

　　10. Lijuan Wan and Feng Ding. Decomposition- and Gradient-Based 
Iterative Identification Algorithms for Multivariable Systems Using the 
Multi-innovation Theory, Circuits, Systems, and Signal Processing, 2019, 
Volume 38, Number 7, Page 2971. [14 CITATIONS]

　　11. Lijuan Liu, Feng Ding, Ling Xu, Jian Pan, Ahmed Alsaedi and 
Tasawar Hayat. Maximum Likelihood Recursive Identification for the 
Multivariate Equation-Error Autoregressive Moving Average Systems 
Using the Data Filtering,  IEEE Access, 2019, Volume 7, Page 41154. [1 
CITATIONS].

　　12. Qinyao Liu and Feng Ding. Auxiliary Model-Based Recursive 
Generalized Least Squares Algorithm for Multivariate Output-Error 
Autoregressive Systems Using the Data Filtering. Circuits, Systems, and 
Signal Processing, 2019, Volume 38, Number 2, Page 590. [22 
CITATIONS]. 

　　13. Ting Cui, Feng Ding, Ahmed Alsaedi and Tasawar Hayat. 
Recursive parameter and state estimation methods for observability 
canonical state-space models exploiting the hierarchical identification 
principle, IET Control Theory & Applications, 2019, Volume 13, Number 
16, Page 2538. [0 CITATIONS]

　　14. Huan Xu, Lijuan Wan, Feng Ding, Ahmed Alsaedi and Tasawar 
Hayat. Fitting the exponential autoregressive model through recursive 
search, Journal of the Franklin Institute, 2019, Volume 356, Number 11, 
Page 5801. [1 CITATIONS]

　　15. Hao Ma, Jian Pan, Lei Lv, Guanghui Xu, Feng Ding, Ahmed 
Alsaedi and Tasawar Hayat. Recursive Algorithms for Multivariable 
Output-Error-Like ARMA Systems, Mathematics, 2019, Volume 7, 
Number 6, Page 558. [5 CITATIONS]

　　16. Ling Xu, Feng Ding and Quanmin Zhu, Hierarchical Newton and 
least squares iterative estimation algorithm for dynamic systems by 
transfer functions based on the impulse responses. International Journal 
of Systems Science, 2019, Volume 50, Number 1, Page 141. [22 
CITATIONS]

　　17. Lijuan Liu, Feng Ding and Quanmin Zhu. Recursive identification 
for multivariate autoregressive equation-error systems with 
autoregressive noise. International Journal of Systems Science, 2018, 
Volume 49, Number 13, Page 2763. [2 CITATIONS]

　　18. Bingbing Shen, Feng Ding, Ling Xu and Tasawar Hayat. Data 
Filtering Based Multi-innovation Gradient Identification Methods for 
Feedback Nonlinear Systems, International Journal of Control, 
Automation and Systems, 2018, Volume 16, Number 5, Page 2225. [1 
CITATIONS]

　　19. Shoupeng Song and Jingjing Shen. Exponential-Reproducing-
Kernel-Based Sparse Sampling Method for Finite Rate of Innovation 
Signal with Arbitrary Pulse Echo Position, Circuits, Systems, and Signal 
Processing, 2019, Volume 38, Number 3, Page 1179. [0 CITATIONS]

　　20. Yuanbiao Hu, Qin Zhou, Hao Yu, Zheng Zhou and Feng Ding. 
Two-Stage Generalized Projection Identification Algorithms for 
Stochastic Systems, Circuits, Systems, and Signal Processing, 2019, 
Volume 38, Number 6, Page 2846. [2 CITATIONS]

　　21. Lijuan Wan, Ximei Liu, Feng Ding and Chunping Chen. 
Decomposition Least-Squares-Based Iterative Identification Algorithms 
for Multivariable Equation-Error Autoregressive Moving Average Systems,
 Mathematics, 2019, Volume 7, Number 7, Page 609. [2 CITATIONS]

　　22. Junxia Ma, Qiulin Fei and Weili Xiong. Sliding Window Iterative
 Identification of Systems With Asymmetric Preload Nonlinearity Based 
on the Key Term Separation, IEEE Access, 2019, Volume 7, Page 36633. [0
 CITATIONS]

　　23. Huafeng Xia, Yongqing Yang, Feng Ding, Ahmed Alsaedi and 
Tasawar Hayat. Maximum likelihood-based recursive least-squares 
estimation for multivariable systems using the data filtering technique, 
International Journal of Systems Science, 2019, Volume 50, Number 6, 
Page 1121. [0 CITATIONS]

　　24. Mengting Chen, Feng Ding, Ahmed Alsaedi and Tasawar Hayat. 
Iterative Identification Algorithms for Bilinear-in-parameter Systems by 
Using the Over-parameterization Model and the Decomposition, 
International Journal of Control, Automation and Systems, 2018, Volume
 16, Number 6, Page 2634. [2 CITATIONS]

　　25. Jian Pan, Wei Li and Haipeng Zhang. Control Algorithms of 
Magnetic Suspension Systems Based on the Improved Double 
Exponential Reaching Law of Sliding Mode Control, International Journal
 of Control, Automation and Systems, 2018, Volume 16, Number 6, Page 
2878. [38 CITATIONS]

　　26. Guang-Yong Chen, Min Gan, C. L. Philip Chen and Long Chen. A 
Two-Stage Estimation Algorithm Based on Variable Projection Method 
for GPS Positioning, IEEE Transactions on Instrumentation and 
Measurement, 2018, Volume 67, Number 11, Page 2518. [3 CITATIONS]

　　27. Ling Xu, Feng Ding and Feng Ding. Algebraic parameter 
estimation approaches for process control systems from sine responses, 
 2019 Chinese Control And Decision Conference (CCDC), Year: 2019, 
Page 1720. [0 CITATIONS]

　　28. Huan Xu, Feng Ding and Jie Sheng. On some parameter 
estimation algorithms for the nonlinear exponential autoregressive 
model, International Journal of Adaptive Control and Signal Processing, 
2019, Volume 33, Number 6, Page 999. [1 CITATIONS]

　　29. Xiao Zhang, Feng Ding and Erfu Yang, State estimation for 
bilinear systems through minimizing the covariance matrix of the state 
estimation errors. International Journal of Adaptive Control and Signal 
Processing, 2019, Volume 33, Number 7, Page 1157. [7 CITATIONS]

　　30. Yasser Shekofteh, Sajad Jafari, Karthikeyan Rajagopal and Viet-
Thanh Pham. Parameter Identification of Chaotic Systems Using a 
Modified Cost Function Including Static and Dynamic Information of 
Attractors in the State Space, Circuits, Systems, and Signal Processing, 
2019, Volume 38, Number 5, Page 2039. [1 CITATIONS]

　　31. Cheng Wang and Kaicheng Li, Aitken-Based Stochastic Gradient 
Algorithm for ARX Models with Time Delay. Circuits, Systems, and Signal
 Processing, 2019, Volume 38, Number 6, Page 2863.. [0 CITATIONS]

　　32. Ling Xu, Weili Xiong, Ahmed Alsaedi and Tasawar Hayat. 
Hierarchical Parameter Estimation for the Frequency Response Based on
 the Dynamical Window Data, International Journal of Control, 
Automation and Systems, 2018, Volume 16, Number 4, Page 1756. [46 
CITATIONS]

　　33. Qinyao Liu, Feng Ding and Erfu Yang. Parameter estimation 
algorithm for multivariable controlled autoregressive autoregressive 
moving average systems, Digital Signal Processing, 2018, Volume 83, 
Page 323. [4 CITATIONS]

　　34. Qinyao Liu, Feng Ding, Ling Xu and Erfu Yang. Partially coupled 
gradient estimation algorithm for multivariable equation-error 
autoregressive moving average systems using the data filtering 
technique, IET Control Theory & Applications, 2019, Volume 13, Number 
5, Page 642. [11 CITATIONS]

　　35. Huafeng Xia, Yongqing Yang, Feng Ding, Ling Xu and Tasawar 
Hayat. Maximum likelihood gradient-based iterative estimation for 
multivariable systems, IET Control Theory & Applications, 2019, Volume 
13, Number 11, Page 1683. [0 CITATIONS]

　　36. Ya Gu, Jicheng Liu, Xiangli Li, Yongxin Chou and Yan Ji, State 
space model identification of multirate processes with time-delay using
 the expectation maximization. Journal of the Franklin Institute, 2019, 
Volume 356, Number 3, Page 1623. [14 CITATIONS]

　　37. Zhengwei Ge, Feng Ding, Ling Xu, Ahmed Alsaedi and Tasawar 
Hayat. Gradient-based iterative identification method for multivariate 
equation-error autoregressive moving average systems using the 
decomposition technique, Journal of the Franklin Institute, 2019, Volume 
356, Number 3, Page 1658. [17 CITATIONS]

　　38. Ya Gu, Yongxin Chou, Jicheng Liu and Yan Ji. Moving horizon 
estimation for multirate systems with time-varying time-delays, Journal 
of the Franklin Institute, 2019, Volume 356, Number 4, Page 2325. [15 
CITATIONS]

　　39. Ting Cui, Feng Ding, Xiangli Li and Tasawar Hayat. Kalman 
filtering based gradient estimation algorithms for observer canonical 
state-space systems with moving average noises, Journal of the Franklin 
Institute, 2019, Volume 356, Number 10, Page 5485. [0 CITATIONS]

　　40. Jian Pan, Hao Ma, Xiao Jiang, Wenfang Ding and Feng Ding. 
Adaptive Gradient-Based Iterative Algorithm for Multivariable Controlled 
Autoregressive Moving Average Systems Using the Data Filtering 
Technique, Complexity, 2018, Volume 2018, Page 1. [30 CITATIONS]

　　41. Lijuan Liu, Feng Ding, Cheng Wang, Ahmed Alsaedi and Tasawar 
Hayat. Maximum Likelihood Multi-innovation Stochastic Gradient 
Estimation for Multivariate Equation-error Systems, International Journal
 of Control, Automation and Systems, 2018, Volume 16, Number 5, Page 
2528. [0 CITATIONS]

　　42. Yunze Guo, Lijuan Wan, Ling Xu, Feng Ding, Ahmed Alsaedi and 
Tasawar Hayat. Two-stage Recursive Least Squares Parameter Estimation
 Algorithm for Multivariate Output-error Autoregressive Moving Average 
Systems, International Journal of Control, Automation and Systems, 2019,
 Volume 17, Number 6, Page 1547. [0 CITATIONS]

　　43. Siyu Liu, Feng Ding, Ling Xu and Tasawar Hayat. Hierarchical 
Principle-Based Iterative Parameter Estimation Algorithm for Dual-
Frequency Signals, Circuits, Systems, and Signal Processing, 2019, Volume 
38, Number 7, Page 3251. [11 CITATIONS]

　　44. Jie Ding, Jiazhong Chen, Jinxing Lin and Lijuan Wan. Particle 
filtering based parameter estimation for systems with output-error type 
model structures, Journal of the Franklin Institute, 2019, Volume 356, 
Number 10, Page 5521. [11 CITATIONS]

　　45. Mengting Chen and Feng Ding. Iterative Identification of 
Discrete-Time Systems With Bilinear Forms in the Presence of Colored 
Noises Based on the Hierarchical Principle, Journal of Computational and 
Nonlinear Dynamics, 2019, Volume 14, Number 9. [0 CITATIONS]

　　46. Mengting Chen, Feng Ding, Rongming Lin, Ahmed Alsaedi and 
Tasawar Hayat. Parameter estimation for a special class of nonlinear 
systems by using the over-parameterisation method and the linear filter,
 International Journal of Systems Science, 2019, Volume 50, Number 9, 
Page 1689. [0 CITATIONS]

　　47. Longjin Wang, Yan Ji, Lijuan Wan and Ni Bu. Hierarchical 
recursive generalized extended least squares estimation algorithms for a 
class of nonlinear stochastic systems with colored noise, Journal of the 
Franklin Institute, 2019, Volume 356, Number 16, Page 10102. [0 
CITATIONS]

　　48. Mengting Chen, Feng Ding and Erfu Yang. Gradient-based 
iterative parameter estimation for bilinear-in-parameter systems using 
the model decomposition technique, IET Control Theory & Applications, 
2018, Volume 12, Number 17, Page 2380. [2 CITATIONS]


　　49. Ling Xu, Feng Ding and Feng Ding. Proceedings of 2019 Chinese 
Intelligent Systems Conference. Series: Lecture Notes in Electrical 
Engineering, Year: 2020, Volume 594, Page 620. [0 CITATIONS]

　　50. Huan Xu, Feng Ding and Erfu Yang. Modeling a nonlinear 
process using the exponential autoregressive time series model, 
Nonlinear Dynamics, 2019, Volume 95, Number 3, Page 2079. [16 
CITATIONS]

　　51. Xian Lu, Feng Ding, Ahmed Alsaedi and Tasawar Hayat. 
Decomposition-based Gradient Estimation Algorithms for Multivariable 
Equation-error Systems, International Journal of Control, Automation 
and Systems, 2019, Volume 17, Number 8, Page 2037. [0 CITATIONS]

　　52. Huafeng Xia, Yan Ji, Ling Xu and Tasawar Hayat. Maximum 
Likelihood-Based Recursive Least-Squares Algorithm for Multivariable 
Systems with Colored Noises Using the Decomposition Technique, 
Circuits, Systems, and Signal Processing, 2019, Volume 38, Number 3, 
Page 986. [2 CITATIONS]

　　在所有引用这篇论文的58篇论文中，有41篇（[2]-[18], [20]-[21], 
[23]-[24], [27]-[29], [32]-[35], [37], [39]-[43], [45]-[46], [48]-[52] 
）是作者Ling Xu, Feng Ding的论文。另外10篇也是中国大陆作者，只有一篇是
非华裔作者的论文。如果大家再挖掘一下那10篇论文，主要挖掘作者的单位，以
及那些作者有没有与这两位作者共同发表过论文，以及与这两位作者的合作者共
同发表过论文，肯定还会有新的发现。

　　3、第二篇论文的引用和被引用分析

　　作者Jiling Ding也来自于江南大学物联网学院。
　　First Online: 31 August 2017
　　345 Downloads, 42 Citations
　　48 References

　　（一） 参考文献（References）分析

　　该文的参考文献如下：

　　1. A. Cristofaro, S. Pettinari, Fault accommodation for multi-input 
linear sampled-data systems. Int. J. Adapt. Control Signal Process. 29, 835
–854 (2015)

　　2. F. Ding, X.H. Wang, L. Mao, L. Xu, Joint state and multi-innovation 
parameter estimation for time-delay linear systems and its convergence 
based on the Kalman filtering. Digital Signal Process. 62, 211–223 (2017)

　　3. F. Ding, F.F. Wang, L. Xu, T. Hayat, A. Alsaedi, Parameter 
estimation for pseudo-linear systems using the auxiliary model and the 
decomposition technique. IET Control Theory Appl. 11(3), 390–400 (2017)

　　4. F. Ding, F.F. Wang, L. Xu, M.H. Wu, Decomposition based least 
squares iterative identification algorithm for multivariate pseudo-linear 
ARMA systems using the data filtering. J. Frankl. Inst. 354(3), 1321–1339
 (2017)

　　5. F. Ding, L. Xu, Q.M. Zhu, Performance analysis of the generalised 
projection identification for time-varying systems. IET Control Theory 
Appl. 10(18), 2506–02514 (2016)

　　6. L. Feng, M.H. Wu, Q.X. Li et al., Array factor forming for image 
reconstruction of one-dimensional nonuniform aperture synthesis 
radiometers. IEEE Geosci. Remote Sens. Lett. 13(2), 237–241 (2016)

　　7. G.X. Gu, S. Wan, L. Qiu, Networked stabilization for multi-input 
systems over quantized fading channels. Automatica 61, 1–8 (2015)

　　8. Y. Ji, F. Ding, Multiperiodicity and exponential attractivity of neural 
networks with mixed delays. Circuits Syst. Signal Process. 36(6), 2558–
2573 (2017)

　　9. Y. Ji, X.M. Liu, Unified synchronization criteria for hybrid 
switching-impulsive dynamical networks. Circuits Syst. Signal Process. 34
(5), 1499–1517 (2015)

　　10. M.H. Li, X.M. Liu, F. Ding, Least-squares-based iterative and 
gradient-based iterative estimation algorithms for bilinear systems. 
Nonlinear Dyn. 89(1), 197–211 (2017)

　　11. M.H. Li, X.M. Liu, F. Ding, The maximum likelihood least squares 
based iterative estimation algorithm for bilinear systems with 
autoregressive noise. J. Frankl. Inst. 354(12), 4861–4881 (2017)

　　12. M.H. Li, X.M. Liu, F. Ding, The gradient based iterative estimation 
algorithms for bilinear systems with autoregressive noise. Circuits Syst. 
Signal Process. (2017). doi: 10.1007/s00034-017-0527-4

　　13. H. Li, Y. Shi, W. Yan, Distributed receding horizon control of 
constrained nonlinear vehicle formations with guaranteed   gamma-gain 
stability. Automatica 68, 148–154 (2016)

　　14. H. Li, Y. Shi, W. Yan, On neighbor information utilization in 
distributed receding horizon control for consensus-seeking. IEEE Trans. 
Cybern. 46(9), 2019–2027 (2016)

　　15. H. Li, W.S. Yan, Y. Shi, Continuous-time model predictive control 
of under-actuated spacecraft with bounded control torques. Automatica 
75, 144–153 (2016)

　　16. J.H. Li, W.X. Zheng, J.P. Gu, L. Hua, Parameter estimation 
algorithms for Hammerstein output error systems using Levenberg–
Marquardt optimization method with varying interval measurements. J. 
Frankl. Inst. 354(1), 316–331 (2017)

　　17. X.G. Liu, J. Lu, Least squares based iterative identification for a 
class of multirate systems. Automatica 46(3), 549–554 (2010)

　　18. Y.W. Mao, F. Ding, Multi-innovation stochastic gradient 
identification for Hammerstein controlled autoregressive systems based 
on the filtering technique. Nonlinear Dyn. 79(3), 1745–1755 (2015)

　　19. D.D. Meng, Recursive least squares and multi-innovation gradient 
estimation algorithms for bilinear stochastic systems. Circuits Syst. Signal 
Process. 35(3), 1052–1065 (2016)

　　20. G. Mercère, L. Bako, Parameterization and identification of 
multivariable state-space systems: a canonical approach. Automatica 47
(8), 1547–1555 (2011)

　　21. S. Mobayen, An LMI-based robust tracker for uncertain linear 
systems with multiple time-varying delays using optimal composite 
nonlinear feedback technique. Nonlinear Dyn. 80, 917–927 (2015)

　　22. J. Na, G. Herrmann, K.Q. Zhang, Improving transient performance 
of adaptive control via a modified reference model and novel adaptation.
 Int. J. Robust Nonlinear Control 27(8), 1351–1372 (2017)

　　23. J. Na, M.N. Mahyuddin, G. Herrmann et al., Robust adaptive 
finite-time parameter estimation and control for robotic systems. Int. J. 
Robust Nonlinear Control 25(16), 3045–3071 (2015)

　　24. J. Na, J. Yang, X.M. Ren et al., Robust adaptive estimation of 
nonlinear system with time-varying parameters. Int. J. Adapt. Control 
Signal Process. 29(8), 1055–1072 (2015)

　　25. J. Na, J. Yang, X. Wu et al., Robust adaptive parameter estimation 
of sinusoidal signals. Automatica 53, 376–384 (2015)

　　26. A. Nasirin, S.K. Nguang, A. Swain, Adaptive sliding mode control 
for a class of MIMO nonlinear systems with uncertainties. J. Frankl. Inst. 
351(4), 2048–2061 (2014)

　　27. J. Pan, X. Jiang, X.K. Wan, W.F. Ding, A filtering based multi-
innovation extended stochastic gradient algorithm for multivariable 
control systems. Int. J. Control Autom. Syst. 15(3), 1189–1197 (2017)

　　28. J. Pan, X.H. Yang, H.F. Cai, B.X. Mu, Image noise smoothing using
 a modified Kalman filter. Neurocomputing 173, 1625–1629 (2016)

　　29. X.K. Wan, Y. Li, C. Xia, M.H. Wu, J. Liang, N. Wang, A T-wave 
alternans assessment method based on least squares curve fitting 
technique. Measurement 86, 93–100 (2016)

　　30. Y.J. Wang, F. Ding, Recursive parameter estimation algorithms 
and convergence for a class of nonlinear systems with colored noise. 
Circuits Syst. Signal Process. 35(10), 3461–3481 (2016)

　　31. Y.J. Wang, F. Ding, Recursive least squares algorithm and 
gradient algorithm for Hammerstein–Wiener systems using the data 
filtering. Nonlinear Dyn. 84(2), 1045–1053 (2016)

　　32. Y.J. Wang, F. Ding, Novel data filtering based parameter 
identification for multiple-input multiple-output systems using the 
auxiliary model. Automatica 71, 308–313 (2016)

　　33.Y.J. Wang, F. Ding, The filtering based iterative identification for 
multivariable systems. IET Control Theory Appl. 10(8), 894–902 (2016)

　　34. X.H. Wang, F. Ding, Convergence of the recursive identification 
algorithms for multivariate pseudo-linear regressive systems. Int. J. 
Adapt. Control Signal Process. 30(6), 824–842 (2016)

　　35. X.H. Wang, F. Ding, Joint estimation of states and parameters for 
an input nonlinear state-space system with colored noise using the 
filtering technique. Circuits Syst. Signal Process. 35(2), 481–500 (2016)

　　36. X.H. Wang, F. Ding, Recursive parameter and state estimation for 
an input nonlinear state space system using the hierarchical 
identification principle. Signal Process. 117, 208–218 (2015)

　　37. D.Q. Wang, Hierarchical parameter estimation for a class of 
MIMO Hammerstein systems based on the reframed models. Appl. Math.
 Lett. 57, 13–19 (2016)

　　38. D.Q. Wang, L. Mao, F. Ding, Recasted models based hierarchical 
extended stochastic gradient method for MIMO nonlinear systems. IET 
Control Theory Appl. 11(4), 476–485 (2017)

　　39. H.N. Wu, J.W. Wang, Observer design and output feedback 
stabilization for nonlinear multivariable systems with diffusion PDE-
governed sensor dynamics. Nonlinear Dyn. 72, 615–628 (2013)

　　40. L. Xu, A proportional differential control method for a time-delay 
system using the Taylor expansion approximation. Appl. Math. Comput. 
236, 391–399 (2014)

　　41. L. Xu, Application of the Newton iteration algorithm to the 
parameter estimation for dynamical systems. J. Comput. Appl. Math. 288, 
33–43 (2015)

　　42. L. Xu, The damping iterative parameter identification method for 
dynamical systems based on the sine signal measurement. Signal 
Process. 120, 660–667 (2016)

　　43. L. Xu, The parameter estimation algorithms based on the 
dynamical response measurement data. Adv. Mech. Eng. 9(9) (2017). 

　　44. L. Xu, L. Chen, W.L. Xiong, Parameter estimation and controller 
design for dynamic systems from the step responses based on the 
Newton iteration. Nonlinear Dyn. 79(3), 2155–2163 (2015)

　　45. L. Xu, F. Ding, The parameter estimation algorithms for dynamical 
response signals based on the multi-innovation theory and the 
hierarchical principle. IET Signal Process. 11(2), 228–237 (2017)

　　46. L. Xu, F. Ding, Recursive least squares and multi-innovation 
stochastic gradient parameter estimation methods for signal modeling. 
Circuits Syst. Signal Process. 36(4), 1735–1753 (2017)

　　47. L. Xu, F. Ding, Y. Gu, A. Alsaedi, T. Hayat, A multi-innovation state 
and parameter estimation algorithm for a state space system with d-step
 state-delay. Signal Process. 140, 97–103 (2017)

　　48. N. Zhao, M.H. Wu, J.J. Chen, Android-based mobile educational 
platform for speech signal processing. Int. J. Electr. Eng. Educ. 54(1), 3–16 
(2017)


　　在48篇参考文献中，有28篇是 （2-5，8-12,18, 27, 30-38, 40-47）是 
Feng Ding, Ling Xu, X.H. Wang, D.Q. Wang, Wenfang Ding 的论文。他们
是同一个小组共同发表了论文。在这47篇参考文献中，只有4篇是非中国大陆作
者的论文。

　　（二） 引用（Citations）分析。

　　引用该文的文献如下：

　　1. Jie Ding, Jiazhong Chen, Jinxing Lin and Lijuan Wan. Particle 
filtering based parameter estimation for systems with output-error type 
model structures, Journal of the Franklin Institute, 2019, Volume 356, 
Number 10, Page 5521. [11 CITATIONS]

　　2. Mengting Chen, Feng Ding, Ahmed Alsaedi and Tasawar Hayat. 
Iterative Identification Algorithms for Bilinear-in-parameter Systems by 
Using the Over-parameterization Model and the Decomposition, 
International Journal of Control, Automation and Systems, 2018, Volume 
16, Number 6, Page 2634. [2 CITATIONS]

　　3. Jiling Ding and Weihai Zhang. Recursive least squares based 
hierarchical estimation for multi-input nonlinear systems, Conference: 
2019 Chinese Control And Decision Conference (CCDC), Year: 2019, Page
 4056. [0 CITATIONS]

　　4. Huan Xu, Feng Ding and Jie Sheng. On some parameter 
estimation algorithms for the nonlinear exponential autoregressive 
model, International Journal of Adaptive Control and Signal Processing, 
2019, Volume 33, Number 6, Page 999. [1 CITATIONS]

　　5. Meihang Li, Ximei Liu and Feng Ding. The filtering‐based 
maximum likelihood iterative estimation algorithms for a special class of 
nonlinear systems with autoregressive moving average noise using the 
hierarchical identification principle, International Journal of Adaptive 
Control and Signal Processing, 2019, Volume 33, Number 7, Page 1189. 
[5 CITATIONS]

　　6. Feng Ding, Xiao Zhang and Ling Xu. The innovation algorithms for
 multivariable state‐space models, International Journal of Adaptive 
Control and Signal Processing, 2019, Volume 33, Number 11, Page 1601. 
[0 CITATIONS]

　　7. Feng Ding, Dandan Meng, Jiyang Dai, Qishen Li, Ahmed Alsaedi 
and Tasawar Hayat. Least Squares based Iterative Parameter Estimation 
Algorithm for Stochastic Dynamical Systems with ARMA Noise Using the
 Model Equivalence, International Journal of Control, Automation and 
Systems, 2018, Volume 16, Number 2, Page 630. [28 CITATIONS]]

　　8. Cheng Wang and Kaicheng Li. Aitken-Based Stochastic Gradient 
Algorithm for ARX Models with Time Delay, Circuits, Systems, and Signal
 Processing, 2019, Volume 38, Number 6, Page 2863. [0 CITATIONS]

　　9. Feng Ding, Huibo Chen, Ling Xu, Jiyang Dai, Qishen Li and 
Tasawar Hayat. A hierarchical least squares identification algorithm for 
Hammerstein nonlinear systems using the key term separation, Journal 
of the Franklin Institute, 2018, Volume 355, Number 8, Page 3737. [50 
CITATIONS]

　　10. Ling Xu, Weili Xiong, Ahmed Alsaedi and Tasawar Hayat. 
Hierarchical Parameter Estimation for the Frequency Response Based on 
the Dynamical Window Data, International Journal of Control, 
Automation and Systems, 2018, Volume 16, Number 4, Page 1756. [46 
CITATIONS] 

　　11. Qinyao Liu, Feng Ding and Erfu Yang. Parameter estimation 
algorithm for multivariable controlled autoregressive autoregressive 
moving average systems, Digital Signal Processing, 2018, Volume 83, 
Page 323. [4 CITATIONS]

　　12. Qinyao Liu, Feng Ding, Ling Xu and Erfu Yang. Partially coupled 
gradient estimation algorithm for multivariable equation-error 
autoregressive moving average systems using the data filtering 
technique, IET Control Theory & Applications, 2019, Volume 13, Number 
5, Page 642. [11 CITATIONS] 

　　13. ShuMing He and Yun Lin. Cauchy Distribution Function-
Penalized LMS for Sparse System Identification, Circuits, Systems, and 
Signal Processing, 2019, Volume 38, Number 1, Page 470. [0 CITATIONS]

　　14. Jian Pan, Hao Ma, Xiao Jiang, Wenfang Ding and Feng Ding, 
Adaptive Gradient-Based Iterative Algorithm for Multivariable Controlled 
Autoregressive Moving Average Systems Using the Data Filtering 
Technique, Complexity, 2018, Volume 2018, Page 1. [30 CITATIONS]

　　15. Mengting Chen, Feng Ding, Rongming Lin, Ahmed Alsaedi and 
Tasawar Hayat. Parameter estimation for a special class of nonlinear 
systems by using the over-parameterisation method and the linear filter, 
Journal: International Journal of Systems Science, 2019, Volume 50, 
Number 9, Page 1689. [0 CITATIONS]

　　16. Lijuan Liu, Feng Ding, Cheng Wang, Ahmed Alsaedi and Tasawar 
Hayat. Maximum Likelihood Multi-innovation Stochastic Gradient 
Estimation for Multivariate Equation-error Systems, Journal: International 
Journal of Control, Automation and Systems, 2018, Volume 16, Number 
5, Page 2528. [0 CITATIONS]

　　17. Lijuan Liu, Yan Wang, Cheng Wang, Feng Ding and Tasawar 
Hayat. Maximum likelihood recursive least squares estimation for 
multivariate equation-error ARMA systems, Journal of the Franklin 
Institute, 2018, Volume 355, Number 15, Page 7609. [2 CITATIONS]

　　18. Qinyao Liu, Feng Ding, Yan Wang, Cheng Wang and Tasawar 
Hayat. Auxiliary model based recursive generalized least squares 
identification algorithm for multivariate output-error autoregressive 
systems using the decomposition technique, Journal of the Franklin 
Institute, 2018, Volume 355, Number 15, Page 7643. [1 CITATIONS]

　　19. Yunze Guo, Lijuan Wan, Ling Xu, Feng Ding, Ahmed Alsaedi and 
Tasawar Hayat. Two-stage Recursive Least Squares Parameter Estimation 
Algorithm for Multivariate Output-error Autoregressive Moving Average 
Systems, International Journal of Control, Automation and Systems, 2019, 
Volume 17, Number 6, Page 1547. [0 CITATIONS]

　　20. Siyu Liu, Feng Ding, Ling Xu and Tasawar Hayat. Hierarchical 
Principle-Based Iterative Parameter Estimation Algorithm for Dual-
Frequency Signals, Circuits, Systems, and Signal Processing, 2019, Volume
 38, Number 7, Page 3251. [11 CITATIONS]

　　21. Mengting Chen, Feng Ding and Erfu Yang. Gradient-based 
iterative parameter estimation for bilinear-in-parameter systems using 
the model decomposition technique, IET Control Theory & Applications, 
2018, Volume 12, Number 17, Page 2380. [2 CITATIONS]

　　22. Lijuan Wan, Ximei Liu, Feng Ding and Chunping Chen. 
Decomposition Least-Squares-Based Iterative Identification Algorithms 
for Multivariable Equation-Error Autoregressive Moving Average Systems,
 Mathematics, 2019, Volume 7, Number 7, Page 609. [2 CITATIONS]

　　23. Peiman Davari Dolatabadi, Karen Khanlari, Mohsen Ghafory 
Ashtiany and Mahmood Hosseini. System identification method by using
 inverse solution of equations of motion in time domain and noisy 
condition, Physica A: Statistical Mechanics and its Applications, 2020, 
Volume 538, Page 122680. [0 CITATIONS]

　　24. Xian Lu, Feng Ding, Ahmed Alsaedi and Tasawar Hayat, 
Decomposition-based Gradient Estimation Algorithms for Multivariable 
Equation-error Systems. International Journal of Control, Automation 
and Systems, 2019, Volume 17, Number 8, Page 2037. [0 CITATIONS]

　　25. Huafeng Xia, Yan Ji, Ling Xu and Tasawar Hayat. Maximum 
Likelihood-Based Recursive Least-Squares Algorithm for Multivariable 
Systems with Colored Noises Using the Decomposition Technique, 
Circuits, Systems, and Signal Processing, 2019, Volume 38, Number 3, 
Page 986. [2 CITATIONS]

　　26. Cheng Wang, Kaicheng Li and Shuai Su. Hierarchical Newton 
Iterative Parameter Estimation of a Class of Input Nonlinear Systems 
Based on the Key Term Separation Principle,  Complexity, 2018, Volume 
2018, Page 1. [1 CITATIONS]

　　27. Meihang Li, Ximei Liu and Feng Ding. Filtering-Based Maximum 
Likelihood Gradient Iterative Estimation Algorithm for Bilinear Systems 
with Autoregressive Moving Average Noise, Journal: Circuits, Systems, 
and Signal Processing, 2018, Volume 37, Number 11, Page 5023. [9 
CITATIONS]. 

　　28. Huafeng Xia, Yan Ji, Yanjun Liu and Ling Xu. Maximum 
Likelihood-based Multi-innovation Stochastic Gradient Method for 
Multivariable Systems, International Journal of Control, Automation and 
Systems, 2019, Volume 17, Number 3, Page 565. [1 CITATIONS] 

　　29. Feiyan Chen, Feng Ding, Ling Xu and Tasawar Hayat. Data 
filtering based maximum likelihood extended gradient method for 
multivariable systems with autoregressive moving average noise, Journal 
of the Franklin Institute, 2018, Volume 355, Number 7, Page 3381. [2 
CITATIONS] 

　　30. Ling Xu, Feng Ding and Quanmin Zhu. Hierarchical Newton and 
least squares iterative estimation algorithm for dynamic systems by 
transfer functions based on the impulse responses, International Journal
 of Systems Science, 2019, Volume 50, Number 1, Page 141. [22 
CITATIONS] 

　　31. Rajalakshmi Murugesan, Jeyadevi Solaimalai and Karthik 
Chandran. Computer-Aided Controller Design for a Nonlinear Process 
Using a Lagrangian-Based State Transition Algorithm, Circuits, Systems, 
and Signal Processing, 2019. [0 CITATIONS]

　　32. Qinyao Liu and Feng Ding. Auxiliary Model-Based Recursive 
Generalized Least Squares Algorithm for Multivariate Output-Error 
Autoregressive Systems Using the Data Filtering, Circuits, Systems, and 
Signal Processing, 2019, Volume 38, Number 2, Page 590. [22 CITATIONS] 

　　33. Xiao Zhang, Feng Ding, Ling Xu and Erfu Yang. State filtering-
based least squares parameter estimation for bilinear systems using the 
hierarchical identification principle, IET Control Theory & Applications, 
2018, Volume 12, Number 12, Page 1704. [53 CITATIONS] 

　　34. Ting Cui, Feng Ding, Ahmed Alsaedi and Tasawar Hayat. 
Recursive parameter and state estimation methods for observability 
canonical state-space models exploiting the hierarchical identification 
principle, IET Control Theory & Applications, 2019, Volume 13, Number 
16, Page 2538. [0 CITATIONS]

　　35. Lijuan Liu, Feng Ding and Quanmin Zhu. Recursive identification 
for multivariate autoregressive equation-error systems with 
autoregressive noise, International Journal of Systems Science, 2018, 
Volume 49, Number 13, Page 2763. [2 CITATIONS] 

　　36. Ya Gu, Jicheng Liu, Xiangli Li, Yongxin Chou and Yan Ji. State 
space model identification of multirate processes with time-delay using 
the expectation maximization, Journal of the Franklin Institute, 2019, 
Volume 356, Number 3, Page 1623. [14 CITATIONS] 

　　37. Zhengwei Ge, Feng Ding, Ling Xu, Ahmed Alsaedi and Tasawar 
Hayat. Gradient-based iterative identification method for multivariate 
equation-error autoregressive moving average systems using the 
decomposition technique, Journal of the Franklin Institute, 2019, Volume 
356, Number 3, Page 1658. [17 CITATIONS]

　　38. Ting Cui, Feng Ding, Xiangli Li and Tasawar Hayat. Kalman 
filtering based gradient estimation algorithms for observer canonical 
state-space systems with moving average noises. Journal of the Franklin 
Institute, 2019, Volume 356, Number 10, Page 5485. [0 CITATIONS]

　　39. Bingbing Shen, Feng Ding, Ling Xu and Tasawar Hayat. Data 
Filtering Based Multi-innovation Gradient Identification Methods for 
Feedback Nonlinear Systems, International Journal of Control, 
Automation and Systems, 2018, Volume 16, Number 5, Page 2225. [1 
CITATIONS]

　　40. Yuanbiao Hu, Qin Zhou, Hao Yu, Zheng Zhou and Feng Ding. 
Two-Stage Generalized Projection Identification Algorithms for 
Stochastic Systems, Circuits, Systems, and Signal Processing, 2019, 
Volume 38, Number 6, Page 2846. [2 CITATIONS]

　　41. Junhong Li and Xiao Li, Particle Swarm Optimization Iterative 
Identification Algorithm and Gradient Iterative Identification Algorithm 
for Wiener Systems with Colored Noise.  Complexity, 2018, Volume 2018, 
Page 1. [1 CITATIONS]

　　42. Huafeng Xia, Yongqing Yang, Feng Ding, Ahmed Alsaedi and 
Tasawar Hayat. Maximum likelihood-based recursive least-squares 
estimation for multivariable systems using the data filtering technique, 
International Journal of Systems Science, 2019, Volume 50, Number 6, 
Page 1121. [0 CITATIONS]


　　在总共42次引用中，有35次引用（[2], [3]-[7], [9]-[12], [14]-[22], 
[24]-[25], [27]-[30], [32]-[35], [37]-[42]）是由Feng Ding,Jiling Ding, 
Ling Xu, Junhong Li等合作发表的人引用的。除了1次引用来自非华裔，其他引
用全部来自中国大陆作者。

　　4、第三篇论文的引用和被引用分析

　　作者 Junhong Li, Wei Xing Zheng,Juping Gu, Liang Hua 大多数来自于
南通大学电气工程学院。Wei Xing Zheng的单位是 School of Computing, 
Engineering and Mathematics, Western Sydney University, Sydney, 
Australia。

　　First Online: 20 October  2017
　　369 Downloads, 21 Citations
　　38 References

　　（一） 参考文献（References）分析

　　该文的参考文献如下：

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Wiener and Hammerstein models. Comput. Chem. Eng. 35(12), 2867–
2875 (2011)

　　2. F. Ding, Combined state and least squares parameter estimation 
algorithms for dynamic systems. Appl. Math. Model. 38(1), 403–412 
(2014)

　　3. F. Ding, L. Xu, Q.M. Zhu, Performance analysis of the generalised 
projection identification for time-varying systems. IET Control Theory 
Appl. 10(18), 2506–2514 (2016)

　　4. F. Ding, X.H. Wang, L. Mao, L. Xu, Joint state and multi-innovation
 parameter estimation for time-delay linear systems and its convergence 
based on the Kalman filtering. Digit. Signal Process. 62, 211–223 (2017)

　　5. F. Ding, F.F. Wang, L. Xu, M.H. Wu, Decomposition based least 
squares iterative identification algorithm for multivariate pseudo-linear 
ARMA systems using the data filtering. J. Frankl. Inst. 354(3), 1321–1339 
(2017)

　　6. F. Ding, F.F. Wang, T. Hayat, A. Alsaedi, Parameter estimation for 
pseudo-linear systems using the auxiliary model and the decomposition 
technique. IET Control Theory Appl. 11(3), 390–400 (2017)

　　7. W. Favoreel, B. De Moor, P.V. Overschee, Subspace state space 
system identification for industrial processes. J. Process Control 10(2–3), 
149–155 (2000)

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identification. IEEE Trans. Circuits Syst. I Fundam. Theory Appl. 44(6), 538
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　　11. J. Guo, L.Y. Wang, G. Yin, Y.L. Zhao, J.F. Zhang, Identification of 
Wiener systems with quantized inputs and binary-valued output 
observations. Automatica 78, 280–286 (2017)

　　12. G. Li, C. Wen, W.X. Zheng, Y. Chen, Identification of a class of 
nonlinear autoregressive models with exogenous inputs based on kernel 
machines. IEEE Trans. Signal Process. 59(5), 2146–2159 (2011)

　　13. J.H. Li, F. Ding, G.W. Yang, Maximum likelihood least squares 
identification method for input nonlinear finite impulse response moving 
average systems. Math. Comput. Model. 55(3–4), 442–450 (2012)

　　14. J.H. Li, F. Ding, L. Hua, Maximum likelihood Newton recursive and
 the Newton iterative estimation algorithms for Hammerstein CARAR 
systems. Nonlinear Dyn. 75(1–2), 235–245 (2014)

　　15. J.H. Li, W.X. Zheng, J.P. Gu, L. Hua, Parameter estimation 
algorithms for Hammerstein output error systems using Levenberg–
Marquardt optimization method with varying interval measurements. J. 
Frankl. Inst. 354(1), 316–331 (2017)

　　16. L. Ljung, System Identification: Theory for the User, 2nd edn. 
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　　18. G. Mercère, L. Bako, Parameterization and identification of 
multivariable state-space systems: a canonical approach. Automatica 47
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　　19. G. Mzyk, P. Wachel, Kernel-based identification of Wiener–
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　　21. S. Oblak, I. ?krjanc, Continuous-time Wiener-model predictive 
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　　22. J. Pan, X. Jiang, X.K. Wan, W. Ding, A filtering based multi-
innovation extended stochastic gradient algorithm for multivariable 
control systems. Int. J. Control Autom. Syst. 15(3), 1189–1197 (2017)

　　23. T.B. Sch?n, A. Wills, B. Ninness, System identification of nonlinear 
state-space models. Automatica 47(1), 39–49 (2011)

　　24. G. Shafiee, M.M. Arefi, M.R. Jahed-Motlagh, A.A. Jalali, Nonlinear 
predictive control of a polymerization reactor based on piecewise linear 
Wiener model. Chem. Eng. J. 143(1–3), 282–292 (2008)

　　25. Y. Shi, J.H. Qin, H.S. Ahn, Distributed coordination control and 
industrial applications. IEEE Trans. Ind. Electron. 64(6), 4967–4971 (2017)

　　26. J. Sj?berg, Q.H. Zhang, L. Ljung, A. Benveniste, B. Delyon, P.-Y. 
Glorennec, H. Hjalmarsson, A. Juditsk, Nonlinear black-box modeling in 
system identification: a unified overview. Automatica 31(12), 1691–1724 
(1995)

　　27. T. S?derstr?m, U. Soverini, Errors-in-variables identification using 
maximum likelihood estimation in the frequency domain. Automatica 79,
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　　28. K. Tiels, J. Schoukens, Wiener system identification with 
generalized orthonormal basis functions. Automatica 50(12), 3147–3154 
(2014)

　　29. D.Q. Wang, Y.P. Gao, Recursive maximum likelihood identification 
method for a multivariable controlled autoregressive moving average 
system. IMA J. Math. Control Inf. 33(4), 1015–1031 (2016)

　　30. D.Q. Wang, Z. Zhang, J.Y. Yuan, Maximum likelihood estimation 
method for dual-rate Hammerstein systems. Int. J. Control Autom. Syst. 
15(2), 698–705 (2017)

　　31. X.H. Wang, F. Ding, Joint estimation of states and parameters for 
an input nonlinear state-space system with colored noise using the 
filtering technique. Circuits Syst. Signal Process. 35(2), 481–500 (2016)

　　32. X.H. Wang, F. Ding, Convergence of the recursive identification 
algorithms for multivariate pseudo-linear regressive systems. Int. J. 
Adapt. Control Signal Process. 30(6), 824–842 (2016)

　　33. D. Westwick, M. Verhaegen, Identifying MIMO Wiener systems 
using subspace model identification methods. Signal Process. 52(2), 235–
258 (1996)

　　34. F. Yu, Z.Z. Mao, M.X. Jia, Recursive identification for Hammerstein
–Wiener systems with dead-zone input nonlinearity. J. Process Control 
23(8), 1108–1115 (2013)

　　35. L. Xu, F. Ding, Recursive least squares and multi-innovation 
stochastic gradient parameter estimation methods for signal modeling. 
Circuits Syst. Signal Process. 36(4), 1735–1753 (2017)

　　36. L. Xu, F. Ding, Y. Gu, A. Alsaedi, T. Hayat, A multi-innovation state 
and parameter estimation algorithm for a state space system with d-step
 state-delay. Signal Process. 140, 97–103 (2017)

　　37. W.X. Zhao, H.F. Chen, W.X. Zheng, Recursive identification for 
nonlinear ARX systems based on stochastic approximation algorithm. 
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　　38. W.X. Zhao, W.X. Zheng, E.-W. Bai, A recursive local linear 
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3069 (2013)

　　在这38篇参考文献中，有18篇（2-6, 12-15, 22,29-32，35-38）是作者 
Feng Ding, Ling Xu, Junlong Li, Wei Xing Zheng, Liang Hua, Wenfang 
Ding, D.Q. Wang的自引。 这些人都在不同的论文中是共同作者，相互关联。
其他中国作者的关联关系，未作进一步挖掘。

　　（二） 引用（Citations）分析。

　　引用该文的文献如下：

　　1. Bingbing Shen, Feng Ding, Ling Xu and Tasawar Hayat. Data 
Filtering Based Multi-innovation Gradient Identification Methods for 
Feedback Nonlinear Systems, International Journal of Control, 
Automation and Systems, 2018, Volume 16, Number 5, Page 2225. [1 
CITATIONS]

　　2. Cheng Wang, Kaicheng Li and Shuai Su. Hierarchical Newton 
Iterative Parameter Estimation of a Class of Input Nonlinear Systems 
Based on the Key Term Separation Principle Journal: Complexity, 2018, 
Volume 2018, Page 1. [1 CITATIONS]

　　3. Qinyao Liu, Feng Ding, Ling Xu and Erfu Yang. Partially coupled 
gradient estimation algorithm for multivariable equation-error 
autoregressive moving average systems using the data filtering 
technique,  IET Control Theory & Applications, 2019, Volume 13, Number 
5, Page 642. [11 CITATIONS]

　　4. Huafeng Xia, Yongqing Yang, Feng Ding, Ling Xu and Tasawar 
Hayat. Maximum likelihood gradient-based iterative estimation for 
multivariable systems, IET Control Theory & Applications, 2019, Volume 
13, Number 11, Page 1683. [0 CITATIONS]

　　5. Ting Cui, Feng Ding, Xiangli Li and Tasawar Hayat. Kalman filtering
 based gradient estimation algorithms for observer canonical state-space
 systems with moving average noises, Journal of the Franklin Institute, 
2019, Volume 356, Number 10, Page 5485. [0 CITATIONS]

　　6. Siyu Liu, Feng Ding, Ling Xu and Tasawar Hayat. Hierarchical 
Principle-Based Iterative Parameter Estimation Algorithm for Dual-
Frequency Signals, Circuits, Systems, and Signal Processing, 2019, Volume
 38, Number 7, Page 3251. [11 CITATIONS]

　　7. Rajalakshmi Murugesan, Jeyadevi Solaimalai and Karthik 
Chandran. Computer-Aided Controller Design for a Nonlinear Process 
Using a Lagrangian-Based State Transition Algorithm, Circuits, Systems, 
and Signal Processing, 2019. [0 CITATIONS]

　　8. Asma Atitallah, Sa?da Bedoui and Kamel Abderrahim. Joint 
Parameter and Time-Delay Identification Algorithm and Its Convergence
 Analysis for Wiener Time-Delay Systems, Circuits, Systems, and Signal 
Processing, 2019. [0 CITATIONS]

　　9. Mengting Chen, Feng Ding and Erfu Yang. Gradient-based 
iterative parameter estimation for bilinear-in-parameter systems using 
the model decomposition technique, IET Control Theory & Applications,
 2018, Volume 12, Number 17, Page 2380. [2 CITATIONS]

　　10. Junhong Li and Xiao Li. Particle Swarm Optimization Iterative 
Identification Algorithm and Gradient Iterative Identification Algorithm 
for Wiener Systems with Colored Noise, Complexity, 2018, Volume 2018, 
Page 1. [1 CITATIONS]

　　11. Tiancheng Zong, Junhong Li, Xiao Li, Liangliang Shang and 
Xiaojiao Zhang. Parameter identification of Box-Jenkins systems based 
on the particle swarm optimization, Conference: 2019 Chinese Control 
And Decision Conference (CCDC), Year: 2019, Page 1696. [0 CITATIONS]

　　12. Jie Ding, Zhengxin Cao, Jiazhong Chen and Guoping Jiang. 
Weighted Parameter Estimation for Hammerstein Nonlinear ARX 
Systems, Circuits, Systems, and Signal Processing, 2019. [0 CITATIONS]

　　13. Lijuan Wan, Ximei Liu, Feng Ding and Chunping Chen. 
Decomposition Least-Squares-Based Iterative Identification Algorithms 
for Multivariable Equation-Error Autoregressive Moving Average Systems,
 Mathematics, 2019, Volume 7, Number 7, Page 609. [2 CITATIONS]

　　14. Lijuan Liu, Feng Ding and Quanmin Zhu. Recursive identification
 for multivariate autoregressive equation-error systems with 
autoregressive noise, International Journal of Systems Science, 2018, 
Volume 49, Number 13, Page 2763. [2 CITATIONS]

　　15. Ping Ma, Feng Ding and Tasawar Hayat. Multi-innovation 
gradient estimation algorithms for multivariate equation-error 
autoregressive moving average systems based on the filtering technique,
 IET Control Theory & Applications, 2019, Volume 13, Number 13, Page 
2086. [0 CITATIONS]

　　16. Huafeng Xia, Yongqing Yang, Feng Ding, Ahmed Alsaedi and 
Tasawar Hayat. Maximum likelihood-based recursive least-squares 
estimation for multivariable systems using the data filtering technique,
 International Journal of Systems Science, 2019, Volume 50, Number 6, 
Page 1121. [0 CITATIONS]

　　17. Meihang Li, Ximei Liu and Feng Ding. The filtering‐based 
maximum likelihood iterative estimation algorithms for a special class of 
nonlinear systems with autoregressive moving average noise using the 
hierarchical identification principle, International Journal of Adaptive 
Control and Signal Processing, 2019, Volume 33, Number 7, Page 1189. 
[5 CITATIONS]

　　18. Feng Ding, Xiao Zhang and Ling Xu.  The innovation algorithms 
for multivariable state‐space models, Journal: International Journal of 
Adaptive Control and Signal Processing, 2019, Volume 33, Number 11, 
Page 1601. [0 CITATIONS]

　　19. Jian Pan, Hao Ma, Xiao Jiang, Wenfang Ding and Feng Ding.  
Adaptive Gradient-Based Iterative Algorithm for Multivariable Controlled 
Autoregressive Moving Average Systems Using the Data Filtering 
Technique, Complexity, 2018, Volume 2018, Page 1. [30 CITATIONS]

　　20. Qinyao Liu and Feng Ding. Auxiliary Model-Based Recursive 
Generalized Least Squares Algorithm for Multivariate Output-Error 
Autoregressive Systems Using the Data Filtering, Circuits, Systems, and 
Signal Processing, 2019, Volume 38, Number 2, Page 590. [22 CITATIONS]

　　21. Lijuan Liu, Yan Wang, Cheng Wang, Feng Ding and Tasawar 
Hayat. Maximum likelihood recursive least squares estimation for 
multivariate equation-error ARMA systems, Journal of the Franklin 
Institute, 2018, Volume 355, Number 15, Page 7609. [2 CITATIONS]

　　在21次引用中，有16次（[1, 3-6, 9-11, 13-21]）是Feng Ding, Ling Xu, 
Junhong Li进行引用的。非华裔作者的引用共2次，其他均为中国大陆作者引用。

　　5、结论

　　通过对Circuits, Systems, and Signal Processing 杂志推荐的近期出版的
高引用论文分析发现，这些论文均为江南大学物联网学院丁锋（Feng Ding）及
合作者完成的。研究的课题是传统的课题，作者发表的论文的所谓高引用统计，
实际为作者及合作者疯狂的自我引用造成。这些论文实际上在出版商的网站的下
载率极低。这是一种非常不诚实的学术不端行为。

　　根据上述引用情况分析，Feng Ding应该是中国引用率最高的10人之一。
但是，用这种刷单方式获得的高引用率对评价科学家的学术水平和成果没有一
点点可信度。只有同行评价才是最科学的评价方法。

　　近日，IET Signal Processing 收到了来自江南大学物联网学院的投稿，同
样是研究类似的辨识问题。在prescreening阶段，主编在看了论文摘要后，针
对摘要提出很多批评，建议不在送审。主编也把这篇文章分配给我来做
prescreening（我自2007年以来一直是IET Signal Processing的变为/副编辑）
，我注意到论文引用的40篇参考文献中有10篇是引用Feng Ding的论文，认识
到来自Feng Ding的团队。由于Feng Ding的学术不端行为曾经多次在新语丝曝
光，加上老是研究老套的辨识问题，并没有看到什么实质性创新，我于是建议不
再送审这篇论文。当然，我客气地建议作者改投控制类杂志。今天很高兴，看到
Feng Ding 团队极少或几乎没有在IET Signal Processing 发表什么论文。

(XYS20191113)

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