Title :
An Efficient Multichannel Linear Prediction-Based Blind Equalization Algorithm in Near Common Zeros Condition
Author :
Jae-Mo Yang ; Hong-Goo Kang
Author_Institution :
Dept. of Electr. & Electron. Eng., Yonsei Univ., Seoul, South Korea
Abstract :
This letter proposes an efficient multichannel acoustic channel equalization method under insufficient channel diversity conditions. To overcome an ill-posed problem caused by near common zeros (NCZs) conditions between different channels, a regularization method that restricts the filter norm has been investigated. However, direct application of this method to the linear-predictive multi-input equalization (LIME) method is not effective. To address this situation, this letter puts forth a novel method to disregard the erroneous term of the LIME solution matrix and to increase forced channel diversity (FCD). The accuracy of the proposed equalization filter is compared to that of the conventional regularization method. Experimental results confirm that the NCZs problem can be solved by adopting the proposed methods.
Keywords :
blind equalisers; filtering theory; matrix algebra; speech processing; FCD; LIME solution matrix method; NCZs; equalization filter; filter norm; forced channel diversity; insufficient channel diversity conditions; linear-predictive multiinput equalization method; multichannel acoustic channel equalization method; multichannel linear prediction-based blind equalization algorithm; near common zeros condition; regularization method; speech dereverberation; Acoustics; Blind equalizers; Covariance matrices; Prediction algorithms; Robustness; Signal processing algorithms; Speech; Channel diversity; linear-predictive multi-input equalization; near common zeros; speech dereverberation;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2014.2301831