NDLI: A new class of neural networks suitable for intelligent control

Content Provider	IEEE Xplore Digital Library
Author	Savic, M. Tan, S.-H.
Copyright Year	1989
Description	Author affiliation: Dept. of Electr., Comput., & Syst. Eng., Rensselaer Polytech. Inst., Troy, NY, USA (Savic, M.; Tan, S.-H.)
Abstract	The authors deal with a class of nonlinear neural networks which are capable of forming decision regions of higher complexity than the multilayer perceptron. These nonlinear neural nets have been used in many applications, from nonlinear classification to intelligent control. They have the same feedforward topology as the multilayer perceptron, except that, in certain nodes, a nonlinear operation is performed on the inputs before the sigmoidal function is applied. In many cases, these nonlinear nets have demonstrated higher classification accuracy than comparably sized multilayer perceptrons. In addition, they require a smaller number of nodes to achieve the same accuracy as the multilayer perceptron, thereby reducing the required interconnections among processing elements in circuit implementations. The generation of an appropriate training set from the target function is also discussed. These training procedures can make additional improvements in the performance of the neural net by increasing the classification accuracy and reducing the required training time. Simulation results are presented.
Starting Page	418
Ending Page	423
File Size	356391
Page Count	6
File Format	PDF
ISBN	0818619872
ISSN	21589860
DOI	10.1109/ISIC.1989.238664
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1989-09-25
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Intelligent control Biological neural networks Neurons Multilayer perceptrons Multi-layer neural network Artificial neural networks Biological system modeling Computer networks Systems engineering and theory
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Simulation of hippocampal place cell phenomenon using multilayer perceptrons

Pattern learning by multilayer neural networks trained by a moderatism-based new algorithm

Evolutionary Feature Selection for Spiking Neural Network Pattern Classifiers

Assembling engineering knowledge in a modular multi-layer perceptron neural network

A study of removing hidden neurons in cascade-correlation neural networks

A fast recursive neuronal learning algorithm applied to intelligent control

Discovery of comprehensible symbolic rules in a neural network

Morphological perceptrons

Volterra models and three-layer perceptrons

A new class of neural networks suitable for intelligent control

Similar Documents

Simulation of hippocampal place cell phenomenon using multilayer perceptrons

Pattern learning by multilayer neural networks trained by a moderatism-based new algorithm

Evolutionary Feature Selection for Spiking Neural Network Pattern Classifiers

Assembling engineering knowledge in a modular multi-layer perceptron neural network

A study of removing hidden neurons in cascade-correlation neural networks

A fast recursive neuronal learning algorithm applied to intelligent control

Discovery of comprehensible symbolic rules in a neural network

Morphological perceptrons

Volterra models and three-layer perceptrons

A new class of neural networks suitable for intelligent control