scholarly journals A Correntropy-Based Proportionate Affine Projection Algorithm for Estimating Sparse Channels with Impulsive Noise

Entropy ◽  
2019 ◽  
Vol 21 (6) ◽  
pp. 555 ◽  
Author(s):  
Zhengxiong Jiang ◽  
Yingsong Li ◽  
Xinqi Huang
Keyword(s):  
Wireless Communication ◽  
Impulsive Noise ◽  
Communication Channels ◽  
Projection Algorithm ◽  
Identification Performance ◽  
Affine Projection ◽  
Sparse Channels ◽  
Input Signals ◽  
Simulation Results ◽  
Maximum Correntropy Criterion

A novel robust proportionate affine projection (AP) algorithm is devised for estimating sparse channels, which often occur in network echo and wireless communication channels. The newly proposed algorithm is realized by using the maximum correntropy criterion (MCC) and the data reusing scheme used in AP to overcome the identification performance degradation of the traditional PAP algorithm in impulsive noise environments. The proposed algorithm is referred to as the proportionate affine projection maximum correntropy criterion (PAPMCC) algorithm, which is derived in the context of channel estimation framework. Many simulation results were obtained to verify that the PAPMCC algorithm is superior to early reported AP algorithms with different input signals under impulsive noise environments.

scholarly journals Affine Projection Algorithm Using Regressive Estimated Error

2011 ◽  
Vol 2011 ◽  
pp. 1-5 ◽  
Author(s):  
Shu Zhang ◽  
Yongfeng Zhi
Keyword(s):  
Convergence Rate ◽  
Adaptive Filtering ◽  
Projection Algorithm ◽  
Error Signal ◽  
Affine Projection ◽  
Affine Projection Algorithm ◽  
Fast Convergence Rate ◽  
Simulation Results ◽  
The Stability ◽  
Estimated Error

An affine projection algorithm using regressive estimated error (APA-REE) is presented in this paper. By redefining the iterated error of the affine projection algorithm (APA), a new algorithm is obtained, and it improves the adaptive filtering convergence rate. We analyze the iterated error signal and the stability for the APA-REE algorithm. The steady-state weights of the APA-REE algorithm are proved to be unbiased and consist. The simulation results show that the proposed algorithm has a fast convergence rate compared with the APA algorithm.

scholarly journals Geometric-algebra affine projection adaptive filter

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yuetao Ren ◽  
Yongfeng Zhi ◽  
Jun Zhang
Keyword(s):  
Geometric Algebra ◽  
Adaptive Filters ◽  
Projection Algorithm ◽  
Affine Projection ◽  
Input Signals ◽  
Convergence Performance ◽  
Ill Posed ◽  
The Stability ◽  
Method Of Lagrange Multipliers ◽  
The Cost

AbstractGeometric algebra (GA) is an efficient tool to deal with hypercomplex processes due to its special data structure. In this article, we introduce the affine projection algorithm (APA) in the GA domain to provide fast convergence against hypercomplex colored signals. Following the principle of minimal disturbance and the orthogonal affine subspace theory, we formulate the criterion of designing the GA-APA as a constrained optimization problem, which can be solved by the method of Lagrange Multipliers. Then, the differentiation of the cost function is calculated using geometric calculus (the extension of GA to include differentiation) to get the update formula of the GA-APA. The stability of the algorithm is analyzed based on the mean-square deviation. To avoid ill-posed problems, the regularized GA-APA is also given in the following. The simulation results show that the proposed adaptive filters, in comparison with existing methods, achieve a better convergence performance under the condition of colored input signals.

Study on UWB Channel Equalization with Adaptive Gain Affine Projection Algorithm

2012 ◽  
Vol 220-223 ◽  
pp. 2121-2128
Author(s):  
Yin Xue Li ◽  
Jun Zhang ◽  
Yong Feng Zhi
Keyword(s):  
Convergence Rate ◽  
Channel Equalization ◽  
Projection Algorithm ◽  
Technology Study ◽  
Time Hopping ◽  
Affine Projection ◽  
Affine Projection Algorithm ◽  
Simulation Results ◽  
Uwb Channel ◽  
Better Than

A new equalization technology study with adaptive affine projection algorithm, aiming at the inter symbol interferences in the UWB channels was presented specially for time-hopping UWB (TH-UWB) systems. The computational complexity and convergence rate of the APA-AG algorithm was compared with the traditional algorithms. The simulation results show that this method improves the convergence rate and has a good stability. And the equalizer with the affine projection algorithm using adaptive gain is better than the RLS equalizer and the LMS equalizer.

scholarly journals Diffusion Correntropy Subband Adaptive Filtering (SAF) Algorithm over Distributed Smart Dust Networks

Symmetry ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1335 ◽  
Author(s):  
Ying Guo ◽  
Jingjing Li ◽  
Yingsong Li
Keyword(s):  
Adaptive Filtering ◽  
Impulsive Noise ◽  
Gaussian Kernel ◽  
Sparse System ◽  
Smart Dust ◽  
Input Signals ◽  
Maximum Correntropy Criterion ◽  
Non Gaussian ◽  
Weighted Values ◽  
Dynamic Gain

The diffusion subband adaptive filtering (DSAF) algorithm has attracted much attention in recent years due to its decorrelation ability for colored input signals. In this paper, a modified DSAF algorithm using the symmetry maximum correntropy criterion (MCC) with individual weighting factors is proposed and discussed to combat impulsive noise, which is denoted as the MCC-DSAF algorithm. During the iterations, the negative exponent in the Gaussian kernel of the MCC-DSAF eliminates the interference of outliers to provide a robust performance in non-Gaussian noise environments. Moreover, in order to enhance the convergence for sparse system identifications, a variant of MCC-DSAF named as improved proportionate MCC-DSAF (MCC-IPDSAF) is presented and investigated, which provides a dynamic gain assignment matrix in the MCC-DSAF to adjust the weighted values of each coefficient. Simulation results verify that the newly presented MCC-DSAF and MCC-IPDSAF algorithms are superior to the popular DSAF algorithms.

scholarly journals Robust Adaptive Filtering Algorithm for Self-Interference Cancellation with Impulsive Noise

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 196
Author(s):  
Jun Lu ◽  
Qunfei Zhang ◽  
Wentao Shi ◽  
Lingling Zhang ◽  
Juan Shi
Keyword(s):  
Adaptive Filtering ◽  
Interference Cancellation ◽  
Impulsive Noise ◽  
Weight Vector ◽  
Filtering Algorithm ◽  
Convergence Performance ◽  
Simulation Results ◽  
Robust Adaptive ◽  
Arctangent Cost Function ◽  
Simultaneous Transmission

Self-interference (SI) is usually generated by the simultaneous transmission and reception in the same system, and the variable SI channel and impulsive noise make it difficult to eliminate. Therefore, this paper proposes an adaptive digital SI cancellation algorithm, which is an improved normalized sub-band adaptive filtering (NSAF) algorithm based on the sparsity of the SI channel and the arctangent cost function. The weight vector is hardly updated when the impulsive noise occurs, and the iteration error resulting from impulsive noise is significantly reduced. Another major factor affecting the performance of SI cancellation is the variable SI channel. To solve this problem, the sparsity of the SI channel is estimated with the estimation of the weight vector at each iteration, and it is used to adjust the weight vector. Then, the convergence performance and calculation complexity are analyzed theoretically. Simulation results indicate that the proposed algorithm has better performance than the referenced algorithms.

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