Introduction to Quantum Neural Technologies

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Rinton Press, 2003 - Science - 231 pages
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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.

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About the author (2003)

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).

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