IEEE.org| IEEE Xplore Digital Library| IEEE Standards| IEEE Spectrum| More Sites

Cart (Loading....) | Create Account | 

Close category search window
Author Searchbeta |  Advanced Search  |  Preferences |  Search Tips  |  More Search Options  
 
Browse Conference Publications > Circuits and Systems, 1993., ... Help

An adaptive Bernoulli-Gaussian model based maximum-likelihood channel equalizer for detection of binary sequences

Full Text Sign-In or Purchase

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing! close button
puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Wu-Ton Chen ; Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan ; Chong-Yung Chi

Based on a modified Bernoulli-Gaussian model, an adaptive maximum-likelihood channel equalizer is proposed. It is a block signal processing algorithm for the detection of binary sequences transmitted through an unknown slowly time-varying channel. Both computational load and storage required by the proposed adaptive channel equalizer are linearly rather than exponentially proportional to the size of signal processing block. A simulation example is provided to show that it can simultaneously track the variation of slowly time-varying channels and detect unknown binary sequences well

Published in:
Circuits and Systems, 1993., ISCAS '93, 1993 IEEE International Symposium on

Date of Conference: 3-6 May 1993

Page(s):
231 - 234 vol.1
Meeting Date :
03 May 1993-06 May 1993
Print ISBN:
0-7803-1281-3
INSPEC Accession Number:
4984965
Conference Location :
Chicago, IL
Digital Object Identifier :
10.1109/ISCAS.1993.393700
Product Type:
Conference Publications

IEEE Account

Purchase Details

Profile Information

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.