Abstract
The study of neural networks is a growing interdisciplinary field that takes inspiration from biology and reflects on adaptive, distributed, and mostly nonlinear systems. This paper summarizes the important results in the neural networks theory and discusses applications in such areas as signal processing, pattern recognition, and control systems, The material for this paper has been compiled from published sources, and no originality for the material is claimed. (author)
Citation Formats
Iqbal, K.
Neural Networks for Control and Signal Processing: A Review.
Pakistan: N. p.,
2004.
Web.
Iqbal, K.
Neural Networks for Control and Signal Processing: A Review.
Pakistan.
Iqbal, K.
2004.
"Neural Networks for Control and Signal Processing: A Review."
Pakistan.
@misc{etde_20618796,
title = {Neural Networks for Control and Signal Processing: A Review}
author = {Iqbal, K}
abstractNote = {The study of neural networks is a growing interdisciplinary field that takes inspiration from biology and reflects on adaptive, distributed, and mostly nonlinear systems. This paper summarizes the important results in the neural networks theory and discusses applications in such areas as signal processing, pattern recognition, and control systems, The material for this paper has been compiled from published sources, and no originality for the material is claimed. (author)}
place = {Pakistan}
year = {2004}
month = {Jul}
}
title = {Neural Networks for Control and Signal Processing: A Review}
author = {Iqbal, K}
abstractNote = {The study of neural networks is a growing interdisciplinary field that takes inspiration from biology and reflects on adaptive, distributed, and mostly nonlinear systems. This paper summarizes the important results in the neural networks theory and discusses applications in such areas as signal processing, pattern recognition, and control systems, The material for this paper has been compiled from published sources, and no originality for the material is claimed. (author)}
place = {Pakistan}
year = {2004}
month = {Jul}
}