NDLI: Sensitivity to noise in bidirectional associative memory (BAM)

Content Provider	IEEE Xplore Digital Library
Author	Shengzhi Du Zengqiang Chen Zhuzhi Yuan Xinghui Zhang
Copyright Year	1990
Abstract	Original Hebbian encoding scheme of bidirectional associative memory (BAM) provides a poor pattern capacity and recall performance. Based on Rosenblatt's perceptron learning algorithm, the pattern capacity of BAM is enlarged, and perfect recall of all training pattern pairs is guaranteed. However, these methods put their emphases on pattern capacity, rather than error correction capability which is another critical point of BAM. This paper analyzes the sensitivity to noise in BAM and obtains an interesting idea to improve noise immunity of BAM. Some researchers have found that the noise sensitivity of BAM relates to the minimum absolute value of net inputs (MAV). However, in this paper, the analysis on failure association shows that it is related not only to MAV but also to the variance of weights associated with synapse connections. In fact, it is a positive monotone increasing function of the quotient of MAV divided by the variance of weights. This idea provides an useful principle of improving error correction capability of BAM. Some revised encoding schemes, such as small variance learning for BAM (SVBAM), evolutionary pseudorelaxation learning for BAM (EPRLAB) and evolutionary bidirectional learning (EBL), have been introduced to illustrate the performance of this principle. All these methods perform better than their original versions in noise immunity. Moreover, these methods have no negative effect on the pattern capacity of BAM. The convergence of these methods is also discussed in this paper. If there exist solutions, EPRLAB and EBL always converge to a global optimal solution in the senses of both pattern capacity and noise immunity. However, the convergence of SVBAM may be affected by a preset function.
Sponsorship	IEEE Computational Intelligence Society
Page Count	12
File Size	663136
Starting Page	887
Ending Page	898
File Format	PDF
ISSN	10459227
Volume Number	16
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-07-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Associative memory Magnesium compounds Immune system Neurofeedback Encoding Error correction Biological neural networks Humans Neurons Hebbian theory pattern recognition bidirectional associative memory (BAM) genetic algorithm (GA) neural network noise immunity
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Networks and Communications Computer Science Applications Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Encoding strategy for maximum noise tolerance bidirectional associative memory

An optimization-based design procedure for asymmetric bidirectional associative memories

Optimum learning for bidirectional associative memory in the sense of capacity

Two iterative encoding schemes for bidirectional associative memory

Memory annihilation of structured maps in bidirectional associative memories

On the capacity of intraconnected bidirectional associative memory

Performance analysis of the bidirectional associative memory and an improved model from the matched-filtering viewpoint

Bidirectional associative memories

A new bidirectional associative memory based on distributed representation

Sensitivity to noise in bidirectional associative memory (BAM)

Similar Documents

Encoding strategy for maximum noise tolerance bidirectional associative memory

An optimization-based design procedure for asymmetric bidirectional associative memories

Optimum learning for bidirectional associative memory in the sense of capacity

Two iterative encoding schemes for bidirectional associative memory

Memory annihilation of structured maps in bidirectional associative memories

On the capacity of intraconnected bidirectional associative memory

Performance analysis of the bidirectional associative memory and an improved model from the matched-filtering viewpoint

Bidirectional associative memories

A new bidirectional associative memory based on distributed representation

Sensitivity to noise in bidirectional associative memory (BAM)