Article citationsMore>>

M. Castella, et al., “Quadratic Higher-Order Criteria for Iterative Blind Separation of a MIMO Convolutive Mix- ture of Sources,” IEEE Transactions. Signal Processing, Vol. 55, No. 1, 2007, pp. 218-232. doi:10.1109/TSP.20 06.882113

has been cited by the following article:

• TITLE: A Modified Eigenvector Method for Blind Deconvolution of MIMO Systems Using the Matrix Pseudo-Inversion Lemma

  AUTHORS: Mitsuru Kawamoto, Kiyotaka Kohno, Yujiro Inouye, Koichi Kurumatani

  KEYWORDS: Blind Signal Processing, Blind Deconvolution, Eigenvector Methods, Super-Exponential Mthods, MIMO Systems, Matrix Pseudo-Inversion Lemma

  JOURNAL NAME: Circuits and Systems, Vol.2 No.1, January 27, 2011

  ABSTRACT: Recently we have developed an eigenvector method (EVM) which can achieve the blind deconvolution (BD) for MIMO systems. One of attractive features of the proposed algorithm is that the BD can be achieved by calculating the eigenvectors of a matrix relevant to it. However, the performance accuracy of the EVM depends highly on computational results of the eigenvectors. In this paper, by modifying the EVM, we propose an algorithm which can achieve the BD without calculating the eigenvectors. Then the pseudo-inverse which is needed to carry out the BD is calculated by our proposed matrix pseudo-inversion lemma. Moreover, using a combination of the conventional EVM and the modified EVM, we will show its performances comparing with each EVM. Simulation results will be presented for showing the effectiveness of the proposed methods.