학술논문
Chebyshev polynomial approximation for activation sigmoid function
Document Type
TEXT
Author
Source
Neural network world: international journal on neural and mass-parallel computing and information systems | 2012 Volume:22 | Number:4
Subject
Language
English
Abstract
An alternative polynomial approximation for the activation sigmoid function is developed here. It can considerably simplify the input/output operations of a neural network. The recursive algorithm is found for Chebyshev expansion of all constituting polynomials.