
Multi-Valued and Universal Binary Neurons
Theory, Learning and Applications
Kluwer Academic Publishers
Published on 30. April 2000
Book
Hardback
IV, 276 pages
978-0-7923-7824-2 (ISBN)
Description
Multi-Valued and Universal Binary Neurons
deals with two new types of neurons: multi-valued neurons and universal binary neurons. These neurons are based on complex number arithmetic and are hence much more powerful than the typical neurons used in artificial neural networks. Therefore, networks with such neurons exhibit a broad functionality. They can not only realise threshold input/output maps but can also implement any arbitrary Boolean function. Two learning methods are presented whereby these networks can be trained easily. The broad applicability of these networks is proven by several case studies in different fields of application: image processing, edge detection, image enhancement, super resolution, pattern recognition, face recognition, and prediction. The book is hence partitioned into three almost equally sized parts: a mathematical study of the unique features of these new neurons, learning of networks of such neurons, and application of such neural networks. Most of this work was developed by the first two authors over a period of more than 10 years and was only available in the Russian literature. With this book we present the first comprehensive treatment of this important class of neural networks in the open Western literature.
Multi-Valued and Universal Binary Neurons is intended for anyone with a scholarly interest in neural network theory, applications and learning. It will also be of interest to researchers and practitioners in the fields of image processing, pattern recognition, control and robotics.
Multi-Valued and Universal Binary Neurons is intended for anyone with a scholarly interest in neural network theory, applications and learning. It will also be of interest to researchers and practitioners in the fields of image processing, pattern recognition, control and robotics.
More details
Edition
2000 ed.
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Research
Illustrations
IV, 276 p.
Dimensions
Height: 241 mm
Width: 160 mm
Thickness: 21 mm
Weight
586 gr
ISBN-13
978-0-7923-7824-2 (9780792378242)
DOI
10.1007/978-1-4757-3115-6
Schweitzer Classification
Other editions
Additional editions

Igor Aizenberg | Naum N. Aizenberg | Joos P.L. Vandewalle
Multi-Valued and Universal Binary Neurons
Theory, Learning and Applications
E-Book
03/2013
Springer
€149.79
Available for download

Igor Aizenberg | Naum N. Aizenberg | Joos P.L. Vandewalle
Multi-Valued and Universal Binary Neurons
Theory, Learning and Applications
Book
12/2010
Springer
€160.49
Shipment within 15-20 days
Content
1. Introduction.- 2. Multiple-Valued Threshold Logic and Multi-Valued Neurons.- 3. P-Realizable Boolean Functions and Universal Binary Neurons.- 4. Learning Algorithms.- 5. Cellular Neural Networks with UBN and MVN.- 6. Other Applications of MVN and MVN-based Neural Networks.- 7. Conclusions, Open Problems, Further Work.- References.