Xizhi Shi's Blind Signal Processing: Theory and Practice PDF

By Xizhi Shi

ISBN-10: 364211346X

ISBN-13: 9783642113468

ISBN-10: 3642113478

ISBN-13: 9783642113475

"Blind sign Processing: conception and perform" not just introduces similar basic arithmetic, but additionally displays the various advances within the box, resembling chance density estimation-based processing algorithms, underdetermined types, advanced worth tools, uncertainty of order within the separation of convolutive combinations in frequency domain names, and have extraction utilizing self reliant part research (ICA). on the finish of the e-book, effects from a examine performed at Shanghai Jiao Tong college within the parts of speech sign processing, underwater signs, snapshot function extraction, facts compression, etc are discussed.

This e-book may be of specific curiosity to complex undergraduate scholars, graduate scholars, college teachers and study scientists in comparable disciplines. Xizhi Shi is a Professor at Shanghai Jiao Tong University.

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Amari et al. first presented the contrast function in z-transform domain similar to blind signal separation algorithm using this Property and realized the system’s blind deconvolution through minimizing the contrast function in the time domain. This blind deconvolution algorithm simpliſes into the natural gradient algorithm of blind signal source separation when the unknown system is multi-input multi-output zero-order linear system. This not only points out the algorithm’s relationship between blind signal source separation and the multi-input multi-output linear system’s blind deconvolution but also leads to a conclusion that the corresponding blind deconvolution algorithm has uniformly varying properties similar to the natural gradient algorithm of blind signal source separation.

P ham D T, Garrat P, Jutten C (1992) Separation of a mixtures of independent sources through a maximum likelihood approach. In: Proceedings of EUSIPCO, Brussels, pp 771—774 [19]! Pham D T (1996) Blind separation of instantaneous mixtures of sources via an independent component analysis. IEEE Transactions on Signal Processing 44(11): 2768—2779 [20]! Pham D T, Garat P (1997) Blind separation of mixtures of independent sources through a quasi-maximum likelihood approach. IEEE Transactions on Signal Processing 45(7): 1712—1725 [21]!

It has been tightly linked to several other techniques, including factor analysis [59], principal component analysis [60~63], and projection pursuit [64,65]. Researchers have incorporated both ideas and methodologies others have used, and these tight connections have resulted in many new algorithms. Ƿ34ǹ. As BSP and blind deconvolution can be considered as two special cases of blind identification in a multi-input and multi-output linear invariant system, BSP also has intrinsic connections with blind deconvolution[8,66,67].

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Blind Signal Processing: Theory and Practice by Xizhi Shi

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