ScholarLens Back to search
2002•Unpublished venueRequires access

A class of new criteria for blind deconvolution

Longfei Fan, Hui Ping Zheng, Zha Guangming, Huang Shunji

Open publisher page 0 citations

Abstract

Complex signal and system models are considered in this paper, and a class of new criteria, which is based on the higher-order cumulant, is derived for blind deconvolution. It is pointed out that blind deconvolution may be realized by maximizing or minimizing the normalized cumulant of the system output. This is a new approach to statistical matching for blind deconvolution. As an example, a new blind deconvolution (equalization) algorithm is proposed, and computer simulation results are included to demonstrate the performance of the proposed algorithm.

About this research paper

What this paper is about

Complex signal and system models are considered in this paper, and a class of new criteria, which is based on the higher-order cumulant, is derived for blind deconvolution. It is pointed out that blind deconvolution may be realized by maximizing or minimizing the normalized cumulant of the system output. This is a new approach to statistical matching for blind deconvolution. As an example, a new blind deconvolution (equalization) algorithm is proposed, and computer simulation results are included to demonstrate the performance of the proposed algorithm.

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Complex signal and system models are considered in this paper, and a class of new criteria, which is based on the higher-order cumulant, is derived for blind deconvolution. It is pointed out that blind deconvolution may be realized by maximizing or minimizing the normalized cumulant of the system output. This is a new approach to statistical matching for blind deconvolution. As an example, a new blind deconvolution (equalization) algorithm is proposed, and computer simulation results are included to demonstrate the performance of the proposed algorithm.

Key concepts: Blind deconvolution, Deconvolution, Blind equalization, Computer science, Algorithm, Higher-order statistics, SIGNAL (programming language), Class (philosophy)

Related papers

Related paper 1Related paper 2Related paper 3
Back to paper searchBrowse research topicsOriginal source
A class of new criteria for blind deconvolution — Research Paper | ScholarLens