Activation function study for wavelet network
Carregando...
Data
Orientador
Coorientador
Pós-graduação
Curso de graduação
Título da Revista
ISSN da Revista
Título de Volume
Editor
Tipo
Trabalho apresentado em evento
Direito de acesso
Acesso aberto
Resumo
The main purpose of this paper is to investigate theoretically and experimentally the use of family of Polynomial Powers of the Sigmoid (PPS) Function Networks applied in speech signal representation and function approximation. This paper carries out practical investigations in terms of approximation fitness (LSE), time consuming (CPU Time), computational complexity (FLOP) and representation power (Number of Activation Function) for different PPS activation functions. We expected that different activation functions can provide performance variations and further investigations will guide us towards a class of mappings associating the best activation function to solve a class of problems under certain criteria.
Descrição
Palavras-chave
Computational complexity, Function evaluation, Least squares approximations, Mapping, Performance, Polynomials, Signal processing, Speech, Wavelet transforms, Activation function, Polynomial Powers of Sigmoid, Neural networks
Idioma
Inglês
Citação
Proceedings of SPIE - The International Society for Optical Engineering, v. 3077, p. 690-697.
