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An Adaptive Activation Function for Higher Order Neural Networks

conference contribution
posted on 2023-05-23, 02:56 authored by Shuxiang XuShuxiang Xu, Zhang, M
© Springer-Verlag Berlin Heidelberg 2002. This paper deals with higher order feed-forward neural networks with a new activation function - neuron-adaptive activation function. Experiments with function approximation and stock market movement simulation have been conducted to justify the new activation function. Experimental results have revealed that higher order feed-forward neural networks with the new neuron-adaptive activation function present several advantages over traditional neuron-fixed higher order feed-forward networks such as much reduced network size, faster learning, and more accurate financial data simulation.

History

Publication title

Proceedings / AI 2002: Advances in Artificial Intelligence

Editors

JG Carbonell & Jorg Siekmann

Pagination

356-362

ISBN

3-540-00197-2

Department/School

School of Information and Communication Technology

Publisher

Springer -Verlag

Place of publication

Germany

Event title

15th Australian Joint Conference on Artificial Intelligence Canberra, Australia

Event Venue

Canberra, Australia

Date of Event (Start Date)

2002-12-02

Date of Event (End Date)

2002-12-06

Repository Status

  • Restricted

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