Affine Projection Algorithm Based on Least Mean Fourth Algorithm for System Identification

In the field of signal processing such as system identification, the affine projection algorithm (APA) is extensively implemented. However, running such algorithms in a non-Gaussian scenario may degrade its performance, since the second-order moment cannot extract all information from the signal. To prevent performance degradation of the algorithm in system identification tasks, we propose a novel APA based on least mean fourth (LMF) algorithm. The new algorithm, namely affine projection least mean fourth algorithm (APLMFA) is based on the high-order error power (HOEP) criterion and as such, can achieve improved performance. We also provide a convergence analysis for APLMFA. Numerical simulation results verify the presented APLMFA achieves smaller steady-state error as compared with the state-of-the-art algorithms.

[1]  Eweda Eweda,et al.  Stochastic analysis of the LMS algorithm for cyclostationary colored Gaussian inputs , 2019, Signal Process..

[2]  Nghi H. Tran,et al.  Estimating Shannon and Constrained Capacities of Bernoulli-Gaussian Impulsive Noise Channels in Rayleigh Fading , 2014, IEEE Transactions on Communications.

[3]  Benoit Champagne,et al.  Self-regularized nonlinear diffusion algorithm based on levenberg gradient descent , 2019, Signal Process..

[4]  Charles Soussen,et al.  From Bernoulli–Gaussian Deconvolution to Sparse Signal Restoration , 2011, IEEE Transactions on Signal Processing.

[5]  Nanning Zheng,et al.  Steady-State Mean-Square Error Analysis for Adaptive Filtering under the Maximum Correntropy Criterion , 2014, IEEE Signal Processing Letters.

[6]  Xianzhong Xie,et al.  Combination of affine projection sign algorithms for robust adaptive filtering in non-gaussian impulsive interference , 2014 .

[7]  Guillaume Barrault,et al.  New analytical model for the filtered-x least mean squares algorithm verified through active noise control experiment , 2007 .

[8]  Lu Lu,et al.  Recursive Geman–McClure Estimator for Implementing Second-Order Volterra Filter , 2018, IEEE Transactions on Circuits and Systems II: Express Briefs.

[9]  Haiquan Zhao,et al.  Robust Distributed Diffusion Recursive Least Squares Algorithms With Side Information for Adaptive Networks , 2018, IEEE Transactions on Signal Processing.

[10]  Zhigang Liu,et al.  Diffusion least mean square/fourth algorithm for distributed estimation , 2017, Signal Process..

[11]  Eweda Eweda,et al.  Dependence of the Stability of the Least Mean Fourth Algorithm on Target Weights Non-Stationarity , 2014, IEEE Transactions on Signal Processing.

[12]  Lu Lu,et al.  DCD-Based Recursive Adaptive Algorithms Robust Against Impulsive Noise , 2020, IEEE Transactions on Circuits and Systems II: Express Briefs.

[13]  Lu Lu,et al.  Affine Projection Algorithm-Based High-Order Error Power for Partial Discharge Denoising in Power Cables , 2020, IEEE Transactions on Instrumentation and Measurement.

[14]  Lu Lu,et al.  Diffusion multi-rate LMS algorithm for acoustic sensor networks , 2018, ArXiv.

[15]  F. Javier Toledo,et al.  Two-Step Linear Least-Squares Method For Photovoltaic Single-Diode Model Parameters Extraction , 2018, IEEE Transactions on Industrial Electronics.

[16]  Eweda Eweda,et al.  Global Stabilization of the Least Mean Fourth Algorithm , 2012, IEEE Transactions on Signal Processing.

[17]  Zhigang Liu,et al.  Robust Set-Membership Normalized Subband Adaptive Filtering Algorithms and Their Application to Acoustic Echo Cancellation , 2017, IEEE Transactions on Circuits and Systems I: Regular Papers.

[18]  Meihang Li,et al.  The least squares based iterative algorithms for parameter estimation of a bilinear system with autoregressive noise using the data filtering technique , 2018, Signal Process..

[19]  Jun Yang,et al.  Frequency-Domain Filtered-x LMS Algorithms for Active Noise Control: A Review and New Insights , 2018, Applied Sciences.

[20]  Yuriy V. Zakharov,et al.  Coordinate descent iterations in fast affine projection algorithm , 2005, IEEE Signal Processing Letters.

[21]  Benoit Champagne,et al.  Distributed Nonlinear System Identification in $\alpha$ -Stable Noise , 2018, IEEE Signal Processing Letters.

[22]  Hon Keung Kwan,et al.  Memory improved proportionate affine projection sign algorithm , 2012 .

[23]  W. Marsden I and J , 2012 .

[24]  Hirofumi Taki,et al.  Rapid High-Resolution Wavenumber Extraction from Ultrasonic Guided Waves Using Adaptive Array Signal Processing , 2018 .

[25]  Yuriy V. Zakharov,et al.  Pseudo-Affine Projection Algorithms for Multichannel Active Noise Control , 2007, IEEE Transactions on Audio, Speech, and Language Processing.

[26]  Bernard Widrow,et al.  The least mean fourth (LMF) adaptive algorithm and its family , 1984, IEEE Trans. Inf. Theory.

[27]  Zongsheng Zheng,et al.  Bias-compensated robust set-membership NLMS algorithm against impulsive noises and noisy inputs , 2017 .

[28]  Felix Albu,et al.  Combined echo and noise cancellation based on Gauss-Seidel pseudo affine projection algorithm , 2004, 2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512).

[29]  Rodrigo C. de Lamare,et al.  Sparsity-aware subband adaptive algorithms with adjustable penalties , 2019, Digit. Signal Process..

[30]  Yoshiyuki Yamashita,et al.  Practical application of model identification based on ARX models with transfer functions , 2013 .

[31]  Xinyu Li,et al.  A Robust Diffusion Minimum Kernel Risk-Sensitive Loss Algorithm over Multitask Sensor Networks , 2019, Sensors.

[32]  Yuriy V. Zakharov,et al.  Low-Complexity Implementation of the Affine Projection Algorithm , 2008, IEEE Signal Processing Letters.

[33]  Ali H. Sayed,et al.  Fundamentals Of Adaptive Filtering , 2003 .

[34]  Jiaheng Wang,et al.  Signal Processing for MIMO-NOMA: Present and Future Challenges , 2018, IEEE Wireless Communications.

[35]  Jacob Benesty,et al.  An Affine Projection Sign Algorithm Robust Against Impulsive Interferences , 2010, IEEE Signal Processing Letters.

[36]  Ganapati Panda,et al.  A robust filtered-s LMS algorithm for nonlinear active noise control , 2012 .

[37]  Jinwei Sun,et al.  Improved functional link artificial neural network filters for nonlinear active noise control , 2018, Applied Acoustics.

[38]  D. Giaouris,et al.  Active Online System Identification of Switch Mode DC–DC Power Converter Based on Efficient Recursive DCD-IIR Adaptive Filter , 2012, IEEE Transactions on Power Electronics.

[39]  Eweda Eweda,et al.  Mean-Square Stability Analysis of a Normalized Least Mean Fourth Algorithm for a Markov Plant , 2014, IEEE Transactions on Signal Processing.

[40]  N. Tran,et al.  Optimal Signaling Scheme and Capacity Limit of PLC Under Bernoulli-Gaussian Impulsive Noise , 2015, IEEE Transactions on Power Delivery.

[41]  Yi Yu,et al.  Time delay Chebyshev functional link artificial neural network , 2019, Neurocomputing.

[42]  Ta-Sung Lee,et al.  A variable step-size sign algorithm for channel estimation , 2014, Signal Process..

[43]  PooGyeon Park,et al.  Variable Step-Size Affine Projection Sign Algorithm , 2012, IEEE Transactions on Circuits and Systems II: Express Briefs.