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Introduction gives a glimpse of the quantum neural computation methods and techniques described in later the book. It includes various forms of quantum computation, quantum neural networks and quantum brain models, together with modern adaptive path-integral methods. Its main idea is a combination of quantum linearity and brain-like nonlinearity. It includes the following sections:
This section gives a brief introduction to classical neural dynamical systems.
This section gives a brief introduction to quantum computation.
Discrete Quantum Computers
This section gives a historical overview of quantum computers.
Topological Quantum Computers
This section gives an overview of modern topological quantum computers.
Computation at the Edge of Chaos and Quantum Neural Networks
This section elaborates on the computation at the edge of chaos and introduces quantum neural networks.
Adaptive Path Integral: An Infinite-Dimensional Quantum Neural Network
This section introduces the concept of an adaptive path integral, the most powerful neural computation tool.
Brain Topology vs. Small-World Topology
This section compares and contrasts topological characteristics of neural systems versus social small-world networks.
Quantum Brain and Mind
This section introduces the modern concepts of quantum brain and quantum mind, from the point of view of: neural networks, biophysics, quantum neurodynamics and perception theory.
This section introduces notational conventions used in the book.
KeywordsPartition Function Quantum Computer Central Processing Unit Braid Group Quantum Gate
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