Systematic boolean satisfiability programming in radial basis function neural network

Systematic boolean satisfiability programming in radial basis function neural network

Radial Basis Function Neural Network (RBFNN) is a class of Artificial Neural Network (ANN) that contains hidden layer processing units (neurons) with nonlinear, radially symmetric activation functions. Consequently, RBFNN has extensively suffered from significant computational error and difficulties...

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Bibliographic Details
Main Authors: Mansor, M. A., Jamaludin, S. Z. M., Kasihmuddin, M. S. M., Alzaeemi, S. A., Basir, M. F. M., Sathasivam, S.
Format: Article
Language:English
Published: MDPI AG 2020
Subjects:
QA Mathematics
Online Access:http://eprints.utm.my/87853/1/MohdAsyrafMansor2020_SystematicBooleanSatisfiabilityProgramming.pdf

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http://eprints.utm.my/87853/1/MohdAsyrafMansor2020_SystematicBooleanSatisfiabilityProgramming.pdf

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