Logo image
A Cost Function Level Analysis of Autocorrelation Minimization Based Blind Adaptive Channel Shorteners
Conference proceeding

A Cost Function Level Analysis of Autocorrelation Minimization Based Blind Adaptive Channel Shorteners

Ciira Wa Maina and John MacLaren Walsh
2008 42ND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS, VOLS 1-4, pp 2193-2197
01 Jan 2008

Abstract

Computer Science Computer Science, Interdisciplinary Applications Engineering Engineering, Electrical & Electronic Science & Technology Technology Telecommunications
This paper considers a cost function level analysis of the Sum-squared Autocorrelation Minimization (SAM) channel shortening algorithm. We point out that the actual cost the blind adaptive stochastic gradient descent algorithm is minimizing is only indirectly related to the sum squared autocorrelation. We study the asymptotic regimes under which the actual cost yields a reliable surrogate for the sum squared autocorrelation. We investigate the relationship between the minima of the actual cost and sum squared autocorrelation. We also study the upper bound of the approximate cost as a function of the window size used in the approximate autocorrelation calculation.

Metrics

10 Record Views
3 citations in Scopus

Details

UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#11 Sustainable Cities and Communities

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Web of Science research areas
Computer Science, Interdisciplinary Applications
Engineering, Electrical & Electronic
Telecommunications
Logo image