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Human-Like Biomechanics is a comprehensive introduction into modern geometrical methods to be used as a unified research approach in two apparently separate and rapidly growing fields: mathematical biomechanics and humanoid robotics. The book contains six Chapters and an Appendix. The first Chapter is an Introduction, giving a brief review of mathematical techniques to be used in the text. The second Chapter develops geometrical basis of human-like biomechanics, while the third Chapter develops its mechanical basis, mainly from generalized Lagrangian and Hamiltonian perspective. The fourth Chapter develops topology of human-like biomechanics, while the fifth Chapter reviews related nonlinear control techniques. The sixth Chapter develops covariant biophysics of electro-muscular stimulation. The Appendix consists of two parts: classical muscular mechanics and modern path integral methods, which are both used frequently in the main text. The whole book is based on the authors’ own research papers in human-like biomechanics.

Human mechanics --- Biomechanics --- Robotics --- Mathematical models. --- Medicine. --- Human physiology. --- System theory. --- Physics. --- Statistical physics. --- Dynamical systems. --- Applied mathematics. --- Engineering mathematics. --- Vibration. --- Dynamics. --- Biomedicine. --- Human Physiology. --- Appl.Mathematics/Computational Methods of Engineering. --- Systems Theory, Control. --- Mathematical Methods in Physics. --- Statistical Physics, Dynamical Systems and Complexity. --- Vibration, Dynamical Systems, Control. --- Dynamical systems --- Kinetics --- Mathematics --- Mechanics, Analytic --- Force and energy --- Mechanics --- Physics --- Statics --- Cycles --- Sound --- Engineering --- Engineering analysis --- Mathematical analysis --- Mathematical statistics --- Natural philosophy --- Philosophy, Natural --- Physical sciences --- Dynamics --- Systems, Theory of --- Systems science --- Science --- Human biology --- Medical sciences --- Physiology --- Human body --- Clinical sciences --- Medical profession --- Life sciences --- Pathology --- Physicians --- Statistical methods --- Philosophy --- Automation --- Machine theory --- Biological mechanics --- Mechanical properties of biological structures --- Biophysics --- Contractility (Biology) --- Body mechanics, Human --- Human biomechanics --- Human movements --- Movements, Human --- Animal mechanics --- Human physiology --- Physical anthropology --- Kinesiology --- Systems theory. --- Mathematical physics. --- Mathematical and Computational Engineering. --- Complex Systems. --- Physical mathematics

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If we try to describe real world in mathematical terms, we will see that real life is very often a high–dimensional chaos. Sometimes, by ‘pushing hard’, we manage to make order out of it; yet sometimes, we need simply to accept our life as it is. To be able to still live successfully, we need tounderstand, predict, and ultimately control this high–dimensional chaotic dynamics of life. This is the main theme of the present book. In our previous book, Geometrical - namics of Complex Systems, Vol. 31 in Springer book series Microprocessor– Based and Intelligent Systems Engineering, we developed the most powerful mathematical machinery to deal with high–dimensional nonlinear dynamics. In the present text, we consider the extreme cases of nonlinear dynamics, the high–dimensional chaotic and other attractor systems. Although they might look as examples of complete disorder – they still represent control systems, with their inputs, outputs, states, feedbacks, and stability. Today, we can see a number of nice books devoted to nonlinear dyn- ics and chaos theory (see our reference list). However, all these books are only undergraduate, introductory texts, that are concerned exclusively with oversimpli?ed low–dimensional chaos, thus providing only an inspiration for the readers to actually throw themselves into the real–life chaotic dynamics.

Mechanics, Analytic. --- Dynamics. --- Dynamical systems --- Kinetics --- Mathematics --- Mechanics, Analytic --- Force and energy --- Mechanics --- Physics --- Statics --- Analytical mechanics --- System theory. --- Mathematical physics. --- Engineering mathematics. --- Biomedical engineering. --- Statistical physics. --- Complex Systems. --- Systems Theory, Control. --- Mathematical Methods in Physics. --- Mathematical and Computational Engineering. --- Biomedical Engineering and Bioengineering. --- Statistical Physics and Dynamical Systems. --- Mathematical statistics --- Clinical engineering --- Medical engineering --- Bioengineering --- Biophysics --- Engineering --- Medicine --- Engineering analysis --- Mathematical analysis --- Physical mathematics --- Systems, Theory of --- Systems science --- Science --- Statistical methods --- Philosophy --- Systems theory. --- Dynamical systems. --- Physics. --- Applied mathematics. --- Natural philosophy --- Philosophy, Natural --- Physical sciences --- Dynamics

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Computational Mind: A Complex Dynamics Perspective is a graduate–level monographic textbook in the field of Computational Intelligence. It presents a modern dynamical theory of the computational mind, combining cognitive psychology, artificial and computational intelligence, and chaos theory with quantum consciousness and computation. The book introduces to human and computational mind, comparing and contrasting main themes of cognitive psychology, artificial and computational intelligence. It presents brain/mind dynamics from the chaos theory perspective, including sections on chaos in human EEG, basics of nonlinear dynamics and chaos, techniques of chaos control, synchronization in chaotic systems and complexity in humanoid robots. This book presents modern theory of quantum computational mind, including sections on Dirac–Feynman quantum dynamics, quantum consciousness, and quantum computation using Josephson junctions. The book is designed as a one–semester course for computer scientists, engineers, physicists and applied mathematicians, both in industry and academia. It includes a strong bibliography on the subject and detailed index.

Computational intelligence. --- Dynamics. --- Cognitive psychology. --- Chaotic behavior in systems. --- Intelligence informatique --- Dynamique --- Psychologie cognitive --- Chaos --- Computational intelligence --- Dynamics --- Cognitive psychology --- Chaotic behavior in systems --- Applied Mathematics --- Civil Engineering --- Computer Science --- Engineering & Applied Sciences --- Civil & Environmental Engineering --- Dynamical systems --- Kinetics --- Intelligence, Computational --- Chaos in systems --- Chaos theory --- Chaotic motion in systems --- Psychology, Cognitive --- Medicine. --- Neurosciences. --- Artificial intelligence. --- Statistical physics. --- Dynamical systems. --- Applied mathematics. --- Engineering mathematics. --- Biomedicine. --- Appl.Mathematics/Computational Methods of Engineering. --- Statistical Physics, Dynamical Systems and Complexity. --- Artificial Intelligence (incl. Robotics). --- Cognitive Psychology. --- Cognitive science --- Psychology --- Engineering --- Engineering analysis --- Mathematical analysis --- Mathematics --- Mechanics, Analytic --- Force and energy --- Mechanics --- Physics --- Statics --- Mathematical statistics --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Neural sciences --- Neurological sciences --- Neuroscience --- Medical sciences --- Nervous system --- Clinical sciences --- Medical profession --- Human biology --- Life sciences --- Pathology --- Physicians --- Statistical methods --- Artificial intelligence --- Soft computing --- Differentiable dynamical systems --- Nonlinear theories --- System theory --- Consciousness. --- Mathematical and Computational Engineering. --- Complex Systems. --- Artificial Intelligence. --- Statistical Physics and Dynamical Systems. --- Apperception --- Mind and body --- Perception --- Philosophy --- Spirit --- Self

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Quantum Neural Computation is a graduate-level monographic textbook. It presents a comprehensive introduction, both non-technical and technical, into modern quantum neural computation. Classical computing systems perform classical computations (i.e., Boolean operations, such as AND, OR, NOT gates) using devices that can be described classically (e.g., MOSFETs). On the other hand, quantum computing systems perform classical computations using quantum devices (quantum dots), that is, devices that can be described only using quantum mechanics. Any information transfer between such computing systems involves a state measurement. This book describes this information transfer at the edge of classical and quantum chaos and turbulence, where mysterious quantum-mechanical linearity meets the brain's even more mysterious nonlinear complexity, in order to perform super–high–speed and error–free computations. This volume describes a crossroad between quantum field theory, brain science and computational intelligence.

Computer science. --- Neural networks (Computer science). --- Quantum computers. --- Quantum computers --- Neural networks (Computer science) --- Computer Science --- Mechanical Engineering - General --- Engineering & Applied Sciences --- Mechanical Engineering --- Information Technology --- Artificial Intelligence --- Natural computation. --- Biologically-inspired computing --- Bio-inspired computing --- Natural computing --- Artificial neural networks --- Nets, Neural (Computer science) --- Networks, Neural (Computer science) --- Neural nets (Computer science) --- Artificial intelligence. --- Neurobiology. --- Quantum physics. --- Spintronics. --- Applied mathematics. --- Engineering mathematics. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Appl.Mathematics/Computational Methods of Engineering. --- Quantum Physics. --- Quantum Information Technology, Spintronics. --- Computers --- Bionics --- Electronic data processing --- Artificial intelligence --- Natural computation --- Soft computing --- Quantum theory. --- Artificial Intelligence. --- Mathematical and Computational Engineering. --- Neurosciences --- Quantum dynamics --- Quantum mechanics --- Quantum physics --- Physics --- Mechanics --- Thermodynamics --- Engineering --- Engineering analysis --- Mathematical analysis --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Cognitive science --- Digital computer simulation --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Mathematics --- Fluxtronics --- Magnetoelectronics --- Spin electronics --- Spinelectronics --- Microelectronics --- Nanotechnology

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This graduate-level monographic textbook treats applied differential geometry from a modern scientific perspective. Co-authored by the originator of the world's leading human motion simulator - "Human Biodynamics Engine", a complex, 264-DOF bio-mechanical system, modeled by differential-geometric tools - this is the first book that combines modern differential geometry with a wide spectrum of applications, from modern mechanics and physics, via nonlinear control, to biology and human sciences. The book is designed for a two-semester course, which gives mathematicians a variety of applications

Geometry, Differential. --- Mathematical physics. --- Physical mathematics --- Physics --- Differential geometry --- Mathematics