Language：English   Publishing type：Research paper (scientific journal)  

DOI： https://doi.org/10.1038/s41598-021-96682-0

Publishing type：Research paper (international conference proceedings)  

Publishing type：Research paper (international conference proceedings)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：Japanese   Publishing type：Research paper (scientific journal)  

Publishing type：Research paper (international conference proceedings)  

Language：Japanese   Publishing type：Research paper (scientific journal)  

Language：Japanese   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)   Publisher：IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC  

The matrix inversion lemma gives an explicit formula of the inverse of a positive definite matrix added to a block of dyads ( represented as) as follows: (A + BB(H))(-1) = A(-1) - A(-1) B(I + B(H) A(-1) B)(-1) B(H) A(-1). It is well known in the literature that this formula is very useful to develop a block-based recursive least squares algorithm for the block-based recursive identification of linear systems or the design of adaptive filters. We extend this result to the case when the matrix is singular and present a matrix pseudoinversion lemma along with some illustrative examples. Based on this result, we propose a block-based adaptive multichannel superexponential algorithm. We present simulation results for the performance of the block-based algorithm in order to show the usefulness of the matrix pseudoinversion lemma.

DOI： 10.1109/TCSI.2010.2050222

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

The matrix inversion lemma gives as explicit formula of the inverse of a positive definite matrix A added to a block of dyads (represented as BBH). It is well-known in the literature that this formula is very useful to develop a block-based recursive least-squares algorithm for the block-based recursive identification of linear systems or the design of adaptive filters. We already extended this result to the case when the matrix A is singular, and presented the matrix pseudo-inversion lemma. Such a singular case may occur in a situation where a given problem is overdetermined in the sense that it has more equations than unknowns. In this paper, based on these results, we propose a block-based adaptive multichannel super-exponential deflation algorithm. We present simulation results for the performance of the block-based algorithm in order to show the usefulness of the matrix pseudo-inversion lemma.

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

Recently we have developed an eigenvector method (EVM) which can achieve the blind deconvolution (BD) for MIMO systems. The attractive features of the proposed algorithm are that the BD can be achieved by calculating the eigenvectors of a matrix and by using reference signals. However, the performance accuracy of the EVM depends highly on the computational result 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. Simulation results will be presented for showing the validity of the proposed method.

Language：English   Publishing type：Research paper (international conference proceedings)  

Recently we develop two kinds of approaches, that is, the super-exponential method (SEM) and the eigenvector method (EVM), of which both can achieve the blind deconvolution for MIMO-IIR systems. It is shown that these methods are closely related each other. Based on this fact, we propose a new SEM incorporated with the EVM. Simulation results will be presented for showing the validity of the proposed method. ©2008 IEEE.

DOI： 10.1109/ISCAS.2008.4541369

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

Recently we develop two kinds of approaches, that is, the super-exponential method (SEM) and the eigenvector method (EVM), of which both can achieve the blind deconvolution for MIMO-IIR systems. It is shown that these methods are closely related each other. Based on this fact, we propose a new SEM incorporated with the EVM. Simulation results will be presented for showing the validity of the proposed method.

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：SPRINGER-VERLAG BERLIN  

This paper deals with a blind deconvolution (DB) problem for multiple-input multiple-output infinite impulse response (MIMO-IIR) systems. To solve this problem, we propose an eigenvector algorithm (EVA). In the proposed EVA, two kinds of EVAs are merged so as to give a good performance: One is an EVA and the other is a Robust EVA (REVA) which works with as little sensitive to Gaussian noise as possible. Owing to this combination, two drawbacks of the conventional EVAs can be overcome. Simulation results show the validity of the proposed EVA.

Language：English   Publishing type：Research paper (scientific journal)  

In the simplest case, the matrix inversion lemma gives an explicit formula of the inverse of a positive-definite matrix A added to a rank-one matrix bbH as follows A +bbH)-1= A -1 A-1 b1+ b H A-1 b-1 bH A-1 It is well known in the literature that this formula is very useful to develop a recursive least-squares algorithm for the recursive identification of linear systems or the design of adaptive filters. We extend this result to the case when the matrix A is singular and present a matrix pseudo-inversion lemma along with some illustrative examples. Such a singular case may occur in a situation where a given problem is overdetermined in the sense that it has more equations than unknowns. This lemma is important in its own right, but in order to show the usefulness of the lemma, we apply it to develop an adaptive super-exponential algorithm for the blind deconvolution of multi-input multi-output systems. © 2008 IEEE.

DOI： 10.1109/TCSI.2007.913613

Language：English   Publishing type：Research paper (scientific journal)   Publisher：IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC  

This letter presents an eigenvector algorithm (EVA) for blind deconvolution (BD) of multiple-input multiple-output infinite impulse response (MIMO-IIR) channels (convolutive mixtures), using the idea of reference signals. Differently from the conventional researches on EVAs, the proposed EVA utilizes only one reference signal for recovering all the source signals simultaneously. Computer simulations are presented for demonstrating the effectiveness of the proposed algorithm.

DOI： 10.1109/LSP.2007.906225

Language：English   Publishing type：Research paper (scientific journal)   Publisher：BIRKHAUSER BOSTON INC  

This paper presents eigenvector algorithms (EVAs) for blind deconvolution of multiple-input, multiple-output infinite impulse response channels (convolutive mixtures). An attractive feature of one of the proposed EVAs is that it is insensitive to Gaussian noises which are added to the outputs of the channels; hence, the proposed EVA is referred to as a "robust" eigenvector algorithm. Simulation results show the validity of the proposed EVAs.

DOI： 10.1007/s00034-007-4003-y

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：SPRINGER-VERLAG BERLIN  

We propose an eigenvector algorithm (EVA) with reference signals for blind deconvolution (BD) of multiple-input multiple-output infinite impulse response (MIMO-IIR) channels. Differently from the conventional EVAs, each output of a deconvolver is used as a reference signal, and moreover the BD can be achieved without using whitening techniques. The validity of the proposed EVA is shown comparing with our conventional EVA.

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

The matrix inversion lemma gives an explicit formula of the inverse of a positive-definite matrix A added to a block of dyads (represented as BBH) as follows:
(A + BBH)(-1) = A(-1) - A(-1) B(I + B-H A(-1)B)(-1) B-H A(-1).
It is well-known in the literature that this formula is very useful to develop a block-based recursive least-squares algorithm for the block-based recursive identification of linear systems or the design of adaptive filters.
We extend this result to the case when the matrix A is singular, and present a matrix pseudo-inversion lemma. Based on this result, we propose a block-based adaptive multicahnnel super-exponential algorithm (BAMSEA). We present simulation results for the performance of the block-based algorithm in order to show the usefulness of the matrix pseudo-inversion lemma.

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

This paper presents eigenvector algorithms (EVAs) for blind deconvolution of multiple-input multiple-output infinite impulse response (MIMO-IIR) channels (convolutive mixtures). One of the attractive features of the proposed EVA is that it is insensitive to Gaussian noises which are added to the outputs of the channels; hence the proposed EVA is referred to as a "robust" eigenvector algorithm (REVA). Simulation results show the validity of the REVA.

Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1016/j.sigpro.2006.07.001

Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1093/ietfec/e89-a.5.1495

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

This paper presents an eigenvector algorithm (EVA) derived from a criterion using reference signals, in which the EVA is applied to the blind source separation (BSS) of instantaneous mixtures. The proposed EVA works such that source signals are simultaneously separated from their mixtures. This is a new result, which has not been clarified by the conventional researches. Simulation results show the validity of the proposed EVA.

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

The so called "super-exponential" methods (SEMs) are attractive methods for solving multichannel blind deconvolution problem. The conventional SEMs, however, have such a drawback that they are very sensitive to Gaussian noise. To overcome this drawback, the robust super-exponential method (RSEM) were proposed for single-input single-output infinite impulse response (SISO-IIR) channels and for multi-input multi-output (MIMO) static channels (instantaneous mixtures). While the conventional SEMs use the second- and higher-order cumulants of observations, the RSEM uses only the higher-order cumulants of observations. Since higher-order cumulants are insensitive to Gaussian noise, the RSEM is robust to Gaussian noise. We proposed an RSEM extended to the case of MIMO-IIR channels (convolutive mixtures). To show the validity of the proposed RSEM, some simulation results are presented.

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

The so called "super-exponential" methods (SEMs) are attractive methods for solving multichannel blind deconvolution problem. The conventional SEMs, however, have such a drawback that they are very sensitive to Gaussian noise. To overcome this drawback, the robust super-exponential method (RSEM) were proposed for single-input single-output infinite impulse response (SISO-IIR) channels and for multi-input multi-output (MIMO) static channels (instantaneous mixtures). While the conventional SEMs use the second- and higher-order cumulants of observations, the RSEM uses only the higher-order cumulants of observations. Since higher-order cumulants are insensitive to Gaussian noise, the RSEM is robust to Gaussian noise. We proposed an RSEM extended to the case of MIMO-IIR channels (convolutive mixtures). To show the validity of the proposed RSEM, some simulation results are presented.

Language：Japanese   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

This paper presents an eigenvector algorithm (EVA) derived from a criterion using reference signals, in which the EVA is applied to the blind source separation (BSS) of instantaneous mixtures. The proposed EVA works such that source signals are simultaneously separated from their mixtures. This is a new result, which has not been clarified by the conventional researches. Simulation results show the validity of the proposed EVA.

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

The so called "super-exponential" methods (SEMs) are attractive methods for solving multichannel blind deconvolution problem. The conventional SEiNls, however, have such a drawback that they are very sensitive to Gaussian noise. To overcome this drawback, the robust super-exponential method (RSEM) were proposed for single-input single-output infinite impulse response (SISO-IIR) channels and for multi-input multi-output (MIMO) static channels (instantaneous mixtures). While the conventional SEMs use the second- and higher-order cumulants of observations, the RSEM uses only the higher-order cumulants of observations. Since higher-order cumulants are insensitive to Gaussian noise, the RSEM is robust to Gaussian noise. We proposed an RSEM extended to the case of MIMO-IIR channels (convolutive mixtures). To show the validity of the proposed RSEM, some simulation results are presented.

Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1109/TSCII.2005.852174

Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1109/TSP.2005.845491

Language：English   Publishing type：Research paper (international conference proceedings)  

The multichannel blind deconvolution of finiteimpulse response (FIR) or infinite-impulse response (IIR) channels is investigated using the multichannel super-exponential deflation methods. We propose a new adaptive approach to the multichannel super-exponential deflation methods using the matrix pseudo-inversion lemma (which is extended from the matrix inversion lemma in the full-rank case to the rank-degenerate case) and the higher-order cross correlations of the channel and the equalizer outputs. In order to see the effectiveness of the proposed approach, many computer simulations are carried out for time-invariant MIMO channels along with time-variant MIMO channels. It is shown through computer simulations that the proposed approach is effective for even time-variant channels. © 2005 IEEE.

DOI： 10.1109/ISCAS.2005.1465974

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

The present paper deals with the blind equalization problem of a single-input single-output infinite impulse response (SISO-IIR) system with additive Gaussian noise. To solve the problem, we propose a new "super-exponential method" (SEM). The novel point of the proposed SEM is that even when Gaussian noise is added to the output of the system, the blind equalization can be achieved with as little influence of Gaussian noise as possible; hence the proposed SEM is referred to as a "robust super-exponential method" (RSEM). Simulation results show the validity of the proposed RSEM.

Language：Japanese   Publishing type：Research paper (scientific journal)  

DOI： 10.9746/sicetr1965.41.692

Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1109/LSP.2003.817855

Language：English   Publishing type：Research paper (scientific journal)  

Language：English   Publishing type：Research paper (scientific journal)  

Language：Japanese   Publishing type：Research paper (scientific journal)  

Publishing type：Article, review, commentary, editorial, etc. (scientific journal)  

Language：Japanese   Presentation type：Oral presentation (general)