Extended bidirectional associative memories: A study on poor education

Authors:
S. R. Kannan
Affiliations:
-
Venue:
Mathematical and Computer Modelling: An International Journal
Year:
2005

Citing 6
Cited 3

The capacity of the Hopfield associative memory

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A multivalued bidirectional associative memory operating on a complex domain

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Correlation Matrix Memories

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A general model for bidirectional associative memories

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Two coding strategies for bidirectional associative memory

IEEE Transactions on Neural Networks
Multilayer associative neural networks (MANN's): storage capacity versus perfect recall

IEEE Transactions on Neural Networks

Global exponential periodicity for BAM neural network with periodic coefficients and continuously distributed delays

Computers & Mathematics with Applications
Global Exponential Stability for Impulsive BAM Neural Networks with Distributed Delays on Time Scales

Neural Processing Letters
Existence and Exponential Stability of Multiple Periodic Solutions for a Multidirectional Associative Memory Neural Network

Neural Processing Letters

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Abstract

This paper presents a new approach to analyze or to select the most influential inputs for locating the reason for poor education among rural people, with the use of bidirectional associative memories (BAM). Quantifying the reason for poor education in rural areas can improve the education of rural people. This paper develops a extended BAM (EBAM) ^[^1^], using BAM and it tries to test this method for analyzing the reason for poor eduction in the rural areas. This analysis can be used to determine the method of education for rural people, and it can help to improve the quality or level of education of rural people. So, this paper uses the EBAM with different neurons for the problem of poor education in rural area.