Analysis and synthesis techniques for Hopfield type synchronous discrete time neural networks with application to associative memory

A.N. Michel; J.A. Farrell; H.-F. Sun

doi:10.1109/31.62410

Analysis and synthesis techniques for Hopfield type synchronous discrete time neural networks with application to associative memory

IEEE Transactions on Circuits and Systems ◽

10.1109/31.62410 ◽

1990 ◽

Vol 37 (11) ◽

pp. 1356-1366 ◽

Cited By ~ 73

Author(s):

A.N. Michel ◽

J.A. Farrell ◽

H.-F. Sun

Keyword(s):

Neural Networks ◽

Associative Memory ◽

Discrete Time ◽

Synthesis Techniques ◽

Analysis And Synthesis

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Analysis and synthesis of a class of discrete-time neural networks described on hypercubes

10.1109/iscas.1990.112175 ◽

2002 ◽

Author(s):

A.N. Michel ◽

J. Si ◽

G. Yen

Keyword(s):

Neural Networks ◽

Discrete Time ◽

Analysis And Synthesis

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Analysis and synthesis of a class of discrete-time neural networks with multilevel threshold neurons

IEEE Transactions on Neural Networks ◽

10.1109/72.363445 ◽

1995 ◽

Vol 6 (1) ◽

pp. 105-116 ◽

Cited By ~ 39

Author(s):

J. Si ◽

A.N. Michel

Keyword(s):

Neural Networks ◽

Discrete Time ◽

Analysis And Synthesis

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Stability analysis and synthesis algorithm of a class of discrete-time neural networks

Mathematical and Computer Modelling ◽

10.1016/0895-7177(94)00193-r ◽

1995 ◽

Vol 21 (1-2) ◽

pp. 1-29 ◽

Cited By ~ 5

Author(s):

G.G. Yen ◽

A.N. Michel

Keyword(s):

Neural Networks ◽

Stability Analysis ◽

Discrete Time ◽

Synthesis Algorithm ◽

Analysis And Synthesis

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Capacity of Stable Periodic Solutions in Discrete-Time Bidirectional Associative Memory Neural Networks

IEEE Transactions on Circuits and Systems II Analog and Digital Signal Processing ◽

10.1109/tcsii.2004.829571 ◽

2004 ◽

Vol 51 (6) ◽

pp. 315-319 ◽

Cited By ~ 33

Author(s):

L. Wang ◽

X. Zou

Keyword(s):

Neural Networks ◽

Periodic Solutions ◽

Associative Memory ◽

Discrete Time ◽

Bidirectional Associative Memory ◽

Stable Periodic

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Associative memory design using discrete-time second-order neural networks with local interconnections

IEEE Transactions on Circuits and Systems I Fundamental Theory and Applications ◽

10.1109/81.554334 ◽

1997 ◽

Vol 44 (2) ◽

pp. 153-158 ◽

Cited By ~ 31

Author(s):

M. Brucoli ◽

L. Carnimeo ◽

G. Grassi

Keyword(s):

Neural Networks ◽

Associative Memory ◽

Discrete Time ◽

Second Order ◽

Memory Design

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Discrete-time bidirectional associative memory neural networks with variable delays

Physics Letters A ◽

10.1016/j.physleta.2004.12.026 ◽

2005 ◽

Vol 335 (2-3) ◽

pp. 226-234 ◽

Cited By ~ 87

Author(s):

Jinling Liang ◽

Jinde Cao ◽

Daniel W.C. Ho

Keyword(s):

Neural Networks ◽

Associative Memory ◽

Discrete Time ◽

Bidirectional Associative Memory ◽

Variable Delays

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Analysis and synthesis of a class of discrete-time neural networks with nonlinear interconnections

IEEE Transactions on Circuits and Systems I Fundamental Theory and Applications ◽

10.1109/81.260221 ◽

1994 ◽

Vol 41 (1) ◽

pp. 52-58 ◽

Cited By ~ 13

Author(s):

J. Si ◽

A.N. Michel

Keyword(s):

Neural Networks ◽

Discrete Time ◽

Analysis And Synthesis

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Improvement of discrete-time cellular neural networks for associative memory using 2-dimensional discrete Walsh transform

1998 Fifth IEEE International Workshop on Cellular Neural Networks and their Applications. Proceedings (Cat. No.98TH8359) ◽

10.1109/cnna.1998.685420 ◽

2002 ◽

Author(s):

T. Kamio ◽

H. Asai

Keyword(s):

Neural Networks ◽

Associative Memory ◽

Discrete Time ◽

Cellular Neural Networks ◽

Walsh Transform ◽

Discrete Walsh Transform

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Global Exponential Stability of Discrete-Time Multidirectional Associative Memory Neural Network with Variable Delays

ISRN Discrete Mathematics ◽

10.5402/2012/831715 ◽

2012 ◽

Vol 2012 ◽

pp. 1-10 ◽

Cited By ~ 8

Author(s):

Min Wang ◽

Tiejun Zhou ◽

Xiaolan Zhang

Keyword(s):

Neural Networks ◽

Exponential Stability ◽

Equilibrium Point ◽

Associative Memory ◽

Discrete Time ◽

Global Exponential Stability ◽

Sufficient Condition ◽

Variable Delays ◽

Exponentially Stable ◽

Inequality Technique

A discrete-time multidirectional associative memory neural networks model with varying time delays is formulated by employing the semidiscretization method. A sufficient condition for the existence of an equilibrium point is given. By calculating difference and using inequality technique, a sufficient condition for the global exponential stability of the equilibrium point is obtained. The results are helpful to design global exponentially stable multidirectional associative memory neural networks. An example is given to illustrate the effectiveness of the results.

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