Online SOS-based multichannel blind equalization algorithm with noise

Authors:
Xizhong Shen;Xizhi Shi
Affiliations:
National Key Laboratory for Vibration, Shock and Noise, Shanghai Jiao Tong University, Shanghai, China and School of Mechanical and Automation Engineering, Shanghai Institute of Technology, Shangh ...;National Key Laboratory for Vibration, Shock and Noise, Shanghai Jiao Tong University, Shanghai, China
Venue:
Signal Processing
Year:
2005

Citing 3
Cited 0

Matrix analysis

Matrix analysis
Natural gradient works efficiently in learning

Neural Computation
Equivariant nonstationary source separation

Neural Networks

Quantified Score

Hi-index	0.08

Visualization

Abstract

Multichannel blind equalization is an important task for numerous applications such as speech separation, dereverberation, communication, signal processing and control, etc. In this paper, only second-order statistics is used to construct a cost function and thus a new online algorithm is derived with natural gradient search method for multichannel blind equalization. The proposed algorithm can deal with observations with lower-level noise. Simulations and comparisons indicate the efficiency and ability of the algorithm to perform blind equalization with simple calculation, fast convergence speed and high accuracy, and also can carry out speech separation and dereverberation.