The window least mean square error algorithm

In order to improve the performance of LMS (least mean square) algorithm by decreasing the amount of calculations this research proposes to make an update on each step only for those elements from the input data set, that fall within a small window W near the separating hyperplane surface. This work...

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Main Author:	Degtyarena, Anna Semenovna
Format:	Others
Published:	CSUSB ScholarWorks 2003
Subjects:	Least squares Computer algorithms Neural networks (Computer science) Artificial intelligence Expert systems (Computer science) Perceptrons Theory and Algorithms
Online Access:	https://scholarworks.lib.csusb.edu/etd-project/2385 https://scholarworks.lib.csusb.edu/cgi/viewcontent.cgi?article=3386&context=etd-project

id	ndltd-csusb.edu-oai-scholarworks.lib.csusb.edu-etd-project-3386
record_format	oai_dc
spelling	ndltd-csusb.edu-oai-scholarworks.lib.csusb.edu-etd-project-33862019-10-23T03:32:37Z The window least mean square error algorithm Degtyarena, Anna Semenovna In order to improve the performance of LMS (least mean square) algorithm by decreasing the amount of calculations this research proposes to make an update on each step only for those elements from the input data set, that fall within a small window W near the separating hyperplane surface. This work aims to describe in detail the results that can be achieved by using the proposed LMS with window learning algorithm in information systems that employ the methodology of neural network for the purposes of classification. 2003-01-01T08:00:00Z text application/pdf https://scholarworks.lib.csusb.edu/etd-project/2385 https://scholarworks.lib.csusb.edu/cgi/viewcontent.cgi?article=3386&context=etd-project Theses Digitization Project CSUSB ScholarWorks Least squares Computer algorithms Neural networks (Computer science) Artificial intelligence Expert systems (Computer science) Perceptrons Theory and Algorithms
collection	NDLTD
format	Others
sources	NDLTD
topic	Least squares Computer algorithms Neural networks (Computer science) Artificial intelligence Expert systems (Computer science) Perceptrons Theory and Algorithms
spellingShingle	Least squares Computer algorithms Neural networks (Computer science) Artificial intelligence Expert systems (Computer science) Perceptrons Theory and Algorithms Degtyarena, Anna Semenovna The window least mean square error algorithm
description	In order to improve the performance of LMS (least mean square) algorithm by decreasing the amount of calculations this research proposes to make an update on each step only for those elements from the input data set, that fall within a small window W near the separating hyperplane surface. This work aims to describe in detail the results that can be achieved by using the proposed LMS with window learning algorithm in information systems that employ the methodology of neural network for the purposes of classification.
author	Degtyarena, Anna Semenovna
author_facet	Degtyarena, Anna Semenovna
author_sort	Degtyarena, Anna Semenovna
title	The window least mean square error algorithm
title_short	The window least mean square error algorithm
title_full	The window least mean square error algorithm
title_fullStr	The window least mean square error algorithm
title_full_unstemmed	The window least mean square error algorithm
title_sort	window least mean square error algorithm
publisher	CSUSB ScholarWorks
publishDate	2003
url	https://scholarworks.lib.csusb.edu/etd-project/2385 https://scholarworks.lib.csusb.edu/cgi/viewcontent.cgi?article=3386&context=etd-project
work_keys_str_mv	AT degtyarenaannasemenovna thewindowleastmeansquareerroralgorithm AT degtyarenaannasemenovna windowleastmeansquareerroralgorithm
_version_	1719275290457276416

The window least mean square error algorithm

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