Pii: S0165-1684(01)00108-6
نویسنده
چکیده
‘Bussgang’ deconvolution techniques for blind digital channels equalization rely on a Bayesian estimator of the source sequence de1ned on the basis of channel=equalizer cascade model which involves the de1nition of deconvolution noise. In this paper we consider four ‘Bussgang’ blind deconvolution algorithms for uniformly distributed source signals and investigate their numerical performances as well as some of their analytical features. Particularly, we show that the algorithm, introduced by the present author, provided by a #exible (neuromorphic) estimator is e4ective as it does not require to make any hypothesis about convolutional noise level and exhibits satisfactory numerical performances. ? 2001 Elsevier Science B.V. All rights reserved.
منابع مشابه
A contribution to (neuromorphic) blind deconvolution by flexible approximated Bayesian estimation
`Bussgang ' deconvolution techniques for blind digital channels equalization rely on a Bayesian estimator of the source sequence deened on the basis of channel/equalizer cascade model which involves the deenition of deconvolution noise. In this paper we consider four`Bussgang' blind deconvolution algorithms for uniformly-distributed source signals and investigate their numerical performances as...
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تاریخ انتشار 2001