Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Neural Computing and Applications
Published in: Neural Computing and Applications 1/2011

01-02-2011 | Original Article

The effect of weight fault on associative networks

Authors: Andrew Chi-Sing Leung, Pui Fai Sum, Kevin Ho

Published in: Neural Computing and Applications | Issue 1/2011

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

In the past three decades, the properties of associative networks has been extensively investigated. However, most existing results focus on the fault-free networks only. In implementation, network faults can be exhibited in different forms, such as open weight fault and multiplicative weight noise. This paper studies the effect of weight fault on the performance of the bidirectional associative memory (BAM) model when multiplicative weight noise and open weight fault present. Assuming that connection weights are corrupted by these two common fault models, we study how many number of pattern pairs can be stored in a faulty BAM. Since one of important feature of associative network is error correction, we also study the number of pattern pairs can be stored in a faulty BAM when there are some errors in the initial stimulus pattern.
previous article On the learning machine for three dimensional mapping
next article Adaptive huberized support vector machine and its application to microarray classification

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now
Literature
1.
2.
3.
4.
Haines K, Hecht-Nielsen R (1988) A bam with increased information storage capacity. In: Proceedings of the 1988 IEEE international conference on neural networks, pp 181–190
5.
Amari S (1988) Statistical neurodynamics of various versions of correlation associative memory. In: Proceedings of the 1988 IEEE international conference on neural networks, pp 181–190
6.
Oapos SEM, Austin J (1994) An application of an associative memory to the analysis of document images. In: Proceedings of the British machine vision conference
7.
Chau FT, Cheung B, Tam KY, Li LK (1995) Application of a bi-directional associative memory (bam) network in computer assisted learning in chemistry. Comput chem 18(4):359–362CrossRef
8.
Ruz-Hernandez JA, Sanchez EN, Suarez DA (2006) Designing an associative memory via optimal training for fault diagnosis. In: Proceedings of IJCNN’06, pp 4338–4345
9.
Wang YF, Cruz JB, Mulligan JH (1990) Two coding strategies for bidirectional associative memory. IEEE Trans Neural Netw 1:81–92CrossRef
10.
Leung CS (1993) Encoding method for bidirectional associative memory using projection on convex sets. IEEE Trans Neural Netw 4:879–991CrossRef
11.
Leung CS (1994) Optimum learning for bidirectional associative memory in the sense of capacity. IEEE Trans Syst Man Cybern 24:791–796CrossRef
12.
Lenze B (2001) Improving Leung’s bidirectional learning rule for associative memories. IEEE Trans Neural Netw 12:1222–1226CrossRef
13.
Shen D, Cruz JB (2005) Encoding strategy for maximum noise tolerance bidirectional associative memory. IEEE Trans Neural Netw 16:293–300CrossRef
14.
Simpson PK (1990) Higher-ordered and intraconnected bidirectional associative memories. IEEE Trans Syst Man Cybern 20:637–653CrossRef
15.
Leung CS, Chan LW (1997) The behavior of forgetting learning in bidirectional associative memory. Neural Comput 9:385–401MATHCrossRef
16.
Leung CS, Chan LW, Lai E (1997) Stability and statistical properties of second-order bidirectional associative memory. IEEE Trans Neural Netw 8:267–277CrossRef
17.
Burr JB (1991) Digital neural network implementations. Neural Netw Concepts Appl Implement III:237–285
18.
Himavathi S, Anitha D, Muthuramalingam A (2007) Feedforward neural network implementation in fpga using layer multiplexing for effective resource utilization. IEEE Trans Neural Netw 18:880–888CrossRef
19.
Antony MM, Savich W, Areibi S (2007) The impact of arithmetic representation on implementing mlp-bp on fpgas: a study. IEEE Trans Neural Netw 18:240–252CrossRef
20.
Kaneko T, Liu B (1970) Effect of coefficient rounding in floating-point digital filters. IEEE Trans Aerosp Electron Syst AE-7:995–1003
21.
Liu B, Kaneko T (1969) Error angalysis of digital filter realized with floating-point arithemetic. Proc IEEE 57:1735–1747CrossRef
22.
Phatak DS, Koren I (1995) Complete and partial fault tolerance of feedforward neural nets. IEEE Trans Neural Netw 6:446–456CrossRef
23.
Emmerson MD, Damper RI (1993) Determining and improving the fault tolerance of multilayer perceptrons in a pattern-recognition application. IEEE Trans Neural Netw 4:788–793CrossRef
24.
Zhou ZH, Chen SF (2003) Evolving fault-tolerant neural networks. Neural Comput Appl 11:156–160MATHCrossRef
25.
Sing LC, John S (2008) A fault-tolerant regularizer for rbf networks. IEEE Trans Neural Netw 19:493–507CrossRef
26.
Bolt G (1991) Fault models for artificial neural networks. In: 1991 IEEE international joint conference on neural networks, vol 2, pp 1373–1378
27.
Sossa H, Barron R, Vazquez RA (2007) Study of the influence of noise in the values of a median associative memory. In: ICANNGA 2007 (2), NCS 4432
Metadata
Title
The effect of weight fault on associative networks
Authors
Andrew Chi-Sing Leung
Pui Fai Sum
Kevin Ho
Publication date
01-02-2011
Publisher
Springer-Verlag
Published in
Neural Computing and Applications / Issue 1/2011
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-010-0351-2

Other articles of this Issue 1/2011

Neural Computing and Applications 1/2011 Go to the issue

Original Article

Efficient multi-sequence memory with controllable steady-state period and high sequence storage capacity

Original Article

The stochastic approximation method for adaptive Bayesian classifiers: towards online brain–computer interfaces

Original Article

Fuzzy roughness of n-ary hypergroups based on a complete residuated lattice

Original Article

Nonlinear maximum likelihood estimation of electricity spot prices using recurrent neural networks

Original Article

Adaptive huberized support vector machine and its application to microarray classification

Original Article

Bounded robust control of nonlinear systems using neural network–based HJB solution

Premium Partner

    Image Credits