Gaussian perceptron: Experimental results

Taek Mu Kwon

Gaussian perceptron: Experimental results

Taek Mu Kwon

Electrical Engineering

Research output: Contribution to journal › Conference article › peer-review

6 Scopus citations

Abstract

A new neural model which has a Gaussian activation function is presented. This model is referred to as the Gaussian perceptron. For the training of single-layered Gaussian perceptrons, the Guassian perceptron learning algorithm, which is a variant of the conventional perceptron learning algorithm, is presented. The winner-take-all algorithm is proposed as a multilayer training algorithm. A number of examples are presented along with the comparison with backpropagation networks, which demonstrate the performance of Gaussian perceptron networks.

Original language	English (US)
Pages (from-to)	1593-1598
Number of pages	6
Journal	Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
Volume	3
State	Published - Dec 1 1991
Event	Conference Proceedings of the 1991 IEEE International Conference on Systems, Man, and Cybernetics - Charlottesville, VA, USA Duration: Oct 13 1991 → Oct 16 1991

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title = "Gaussian perceptron: Experimental results",

abstract = "A new neural model which has a Gaussian activation function is presented. This model is referred to as the Gaussian perceptron. For the training of single-layered Gaussian perceptrons, the Guassian perceptron learning algorithm, which is a variant of the conventional perceptron learning algorithm, is presented. The winner-take-all algorithm is proposed as a multilayer training algorithm. A number of examples are presented along with the comparison with backpropagation networks, which demonstrate the performance of Gaussian perceptron networks.",

author = "Kwon, \{Taek Mu\}",

year = "1991",

month = dec,

day = "1",

language = "English (US)",

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journal = "Proceedings of the IEEE International Conference on Systems, Man and Cybernetics",

issn = "0884-3627",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "Conference Proceedings of the 1991 IEEE International Conference on Systems, Man, and Cybernetics ; Conference date: 13-10-1991 Through 16-10-1991",

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T1 - Gaussian perceptron

T2 - Conference Proceedings of the 1991 IEEE International Conference on Systems, Man, and Cybernetics

AU - Kwon, Taek Mu

PY - 1991/12/1

Y1 - 1991/12/1

N2 - A new neural model which has a Gaussian activation function is presented. This model is referred to as the Gaussian perceptron. For the training of single-layered Gaussian perceptrons, the Guassian perceptron learning algorithm, which is a variant of the conventional perceptron learning algorithm, is presented. The winner-take-all algorithm is proposed as a multilayer training algorithm. A number of examples are presented along with the comparison with backpropagation networks, which demonstrate the performance of Gaussian perceptron networks.

AB - A new neural model which has a Gaussian activation function is presented. This model is referred to as the Gaussian perceptron. For the training of single-layered Gaussian perceptrons, the Guassian perceptron learning algorithm, which is a variant of the conventional perceptron learning algorithm, is presented. The winner-take-all algorithm is proposed as a multilayer training algorithm. A number of examples are presented along with the comparison with backpropagation networks, which demonstrate the performance of Gaussian perceptron networks.

UR - https://www.scopus.com/pages/publications/0026404307

UR - https://www.scopus.com/pages/publications/0026404307#tab=citedBy

M3 - Conference article

AN - SCOPUS:0026404307

SN - 0884-3627

VL - 3

SP - 1593

EP - 1598

JO - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics

JF - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics

Y2 - 13 October 1991 through 16 October 1991

ER -

Gaussian perceptron: Experimental results

Abstract

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