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We consider an algorithm for finding all solutions in order to clarify all the stable equilibrium points of a hysteresis neural network. The algorithm includes sign test, linear programming test and a novel subroutine that divides the solution domain efficiently. Using the hysteresis network, we synthesize an associative memory whose cross connection parameters are trinalized. Applying the algorithm to the case where 10 desired memories are stored into 77 cells network, we have clarified all the solutions. Especially, we have confirmed that no spurious memory exists as the trinalization is suitable.

- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E82-A No.1 pp.167-172

- Publication Date
- 1999/01/25

- Publicized

- Online ISSN

- DOI

- Type of Manuscript
- PAPER

- Category
- Numerical Analysis and Optimization

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Yuji KOBAYASHI, Kenya JIN'NO, Toshimichi SAITO, "An Algorithm for Finding All Solutions of a Hysteresis Neural Network" in IEICE TRANSACTIONS on Fundamentals,
vol. E82-A, no. 1, pp. 167-172, January 1999, doi: .

Abstract: We consider an algorithm for finding all solutions in order to clarify all the stable equilibrium points of a hysteresis neural network. The algorithm includes sign test, linear programming test and a novel subroutine that divides the solution domain efficiently. Using the hysteresis network, we synthesize an associative memory whose cross connection parameters are trinalized. Applying the algorithm to the case where 10 desired memories are stored into 77 cells network, we have clarified all the solutions. Especially, we have confirmed that no spurious memory exists as the trinalization is suitable.

URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e82-a_1_167/_p

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@ARTICLE{e82-a_1_167,

author={Yuji KOBAYASHI, Kenya JIN'NO, Toshimichi SAITO, },

journal={IEICE TRANSACTIONS on Fundamentals},

title={An Algorithm for Finding All Solutions of a Hysteresis Neural Network},

year={1999},

volume={E82-A},

number={1},

pages={167-172},

abstract={We consider an algorithm for finding all solutions in order to clarify all the stable equilibrium points of a hysteresis neural network. The algorithm includes sign test, linear programming test and a novel subroutine that divides the solution domain efficiently. Using the hysteresis network, we synthesize an associative memory whose cross connection parameters are trinalized. Applying the algorithm to the case where 10 desired memories are stored into 77 cells network, we have clarified all the solutions. Especially, we have confirmed that no spurious memory exists as the trinalization is suitable.},

keywords={},

doi={},

ISSN={},

month={January},}

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TY - JOUR

TI - An Algorithm for Finding All Solutions of a Hysteresis Neural Network

T2 - IEICE TRANSACTIONS on Fundamentals

SP - 167

EP - 172

AU - Yuji KOBAYASHI

AU - Kenya JIN'NO

AU - Toshimichi SAITO

PY - 1999

DO -

JO - IEICE TRANSACTIONS on Fundamentals

SN -

VL - E82-A

IS - 1

JA - IEICE TRANSACTIONS on Fundamentals

Y1 - January 1999

AB - We consider an algorithm for finding all solutions in order to clarify all the stable equilibrium points of a hysteresis neural network. The algorithm includes sign test, linear programming test and a novel subroutine that divides the solution domain efficiently. Using the hysteresis network, we synthesize an associative memory whose cross connection parameters are trinalized. Applying the algorithm to the case where 10 desired memories are stored into 77 cells network, we have clarified all the solutions. Especially, we have confirmed that no spurious memory exists as the trinalization is suitable.

ER -