240 pages, 9x6 inches
November 2003  Hardcover
ISBN 1-58949-032-0
US$50.00

 
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This is a first introductory book in Quantum Neural Technology -- a new and promising area of informatics. Combination of the ideas from quantum computing and neural computing raises the possibility of dramatically decreasing the complexity of neural systems by replacing networks of classical neurons with a single quantum neuron. In the first two chapters, the fundamentals of neural technologies and of quantum computing are presented. In the third chapter, it is outlined how the problems typical for classical neural technology can be solved by using quantum neural technology. This book is very useful to students, teachers, researchers, and engineers,  who are working in informatics or just interested in being briefly aware of it.

Preface
 

Ch.1 Classical Neural Technologies
   1.1 Patterns processing
   1.2 Linear neurons and associations 
   1.3 Threshold neurons and logical gates 
   1.4 Sigmoid neurons and functions approximation
   1.5 Stochastic neurons and memory
   1.6 Potts neurons and optimization
   1.7 Single-class networks
Ch.2 Quantum Mechanics and Quantum Computing
   2.1 Elements of quantum mechanics
   2.2 Elements of quantum computing
   2.3 Quantum computer  		Ch.3 Quantum Neural Technologies
   3.1 Combining neural and quantum domains
   3.2 Quantum associations
   3.3 Quantum realization of Boolean functions 
   3.4 Quantum content-addressable memory
   3.5 Quantum pattern classification
   3.6 Implementation of distributed Oracle
   3.7 Quantum neural function approximation 
   3.8 Neural controllable quantum gates
   3.9 Quantum neurons in physical modeling
Bibliography 
Index 


 
Dr. Alexandr A. Ezhov, head of Quantum Neural Systems Laboratory at Troitsk Institute for Innovation and Fusion Research, Russia, is an expert in particle transport, neural networks and quantum neural technologies. He has published over 50 research papers on invariant imbedding method in neutron transport, theory and applications of artificial neural networks, and quantum neural systems. He is a co-author of the book Neurocomputing and its application in Economics and Business (1999, in Russian). 

Dr. Gennady P. Berman, a staff member of the Theoretical Division at the Los Alamos National Laboratory, is an expert in classical and quantum dynamical systems, dynamical chaos and applications to magnetic and mesoscopic systems, quantum optics and quantum computation. He has published over 150 research papers on classical and quantum dynamical systems, nanotechnology, and dynamics of quantum computation and other areas. He is a co-author of the books Introduction to Quantum Computers (1998), Crossover-time in Quantum Boson and Spin Systems (1994), and Quantum Chaos: A Harmonic Oscillator in Monochromatic Wave (2001).