Equalização Autodidata: Fundamentos, Novas Propostas e Perspectivas<br />DOI: 10.14209/jcis.1995.3

Authors

  • C. A. F. da Rocha
  • J. M. T. Romano

Abstract

Self-learning equalization is a technique for communication channel equalization without the aid of the usual training sequence. This paper provides an overview about three self-learning approaches: the Bussgang Techniques, the High order Statistics (HOS) Techniques and the Predictive Techniques. The latter are based on the linear prediction theory that we have proposed in previous publications. Simulations results compare the performance of the different approaches. These results show the potentiality of the predictive techniques.

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Published

2015-06-16

How to Cite

A. F. da Rocha, C., & M. T. Romano, J. (2015). Equalização Autodidata: Fundamentos, Novas Propostas e Perspectivas<br />DOI: 10.14209/jcis.1995.3. Journal of Communication and Information Systems, 10(1). Retrieved from https://jcis.sbrt.org.br/jcis/article/view/180

Issue

Vol. 10 No. 1 (1995)

Section

Regular Papers

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Received 2015-06-16
Accepted 2015-06-16
Published 2015-06-16