A Data-Reusing Nonlinear Gradient Descent Algorithm for a Class of Complex-Valued Neural Adaptive Filters

Authors:
Andrew I. Hanna;Danilo P. Mandic
Affiliations:
School of Information Systems, University of East Anglia, Norwich, NR4 7TJ, Norfolk, U.K. e-mail: aih@sys.uea.ac.uk;Communications and Signal Processing Group of the Department of Electrical and Electronic Engineering, Imperial College of Science, Technology and Medicine, London, U.K. e-mail: d.mandic@i ...
Venue:
Neural Processing Letters
Year:
2003

Citing 2
Cited 1

Recurrent Neural Networks for Prediction: Learning Algorithms,Architectures and Stability

Recurrent Neural Networks for Prediction: Learning Algorithms,Architectures and Stability
Relationships Between the A Priori and A Posteriori Errors in Nonlinear Adaptive Neural Filters

Neural Computation

A homomorphic neural network for modeling and prediction

Neural Computation

Quantified Score

Hi-index	0.00

Visualization

Abstract

This letter presents a sigma-pi-sigma neural network (SPSNN) structure. The SPSNN can learn to implement static mapping that multilayer neural networks and radial basis function networks usually do. The output of the SPSNN has the sum of product-of-sum ...