John Robert Burger – författare

Gain a new perspective on how the brain works and inspires new avenues for design in computer science and engineering This unique book is the first of its kind to introduce human memory and basic cognition in terms of physical circuits, beginning with the possibilities of ferroelectric behavior of neural membranes, moving to the logical properties of neural pulses recognized as solitons, and finally exploring the architecture of cognition itself. It encourages invention via the methodical study of brain theory, including electrically reversible neurons, neural networks, associative memory systems within the brain, neural state machines within associative memory, and reversible computers in general. These models use standard analog and digital circuits that, in contrast to models that include non-physical components, may be applied directly toward the goal of constructing a machine with artificial intelligence based on patterns of the brain.Writing from the circuits and systems perspective, the author reaches across specialized disciplines including neuroscience, psychology, and physics to achieve uncommon coverage of: Neural membranes Neural pulses and neural memory Circuits and systems for memorizing and recalling Dendritic processing and human learning Artificial learning in artificial neural networks The asset of reversibility in man and machine Electrically reversible nanoprocessors Reversible arithmetic Hamiltonian circuit finders Quantum versus classical Each chapter introduces and develops new material and ends with exercises for readers to put their skills into practice. Appendices are provided for non-experts who want a quick overview of brain anatomy, brain psychology, and brain scanning. The nature of this book, with its summaries of major bodies of knowledge, makes it a most valuable reference for professionals, researchers, and students with career goals in artificial intelligence, intelligent systems, neural networks, computer architecture, and neuroscience.A solutions manual is available for instructors; to obtain a copy please email the editorial department at ialine@wiley.com.

Gain a new perspective on how the brain works and inspires new avenues for design in computer science and engineering

This unique book is the first of its kind to introduce human memory and basic cognition in terms of physical circuits, beginning with the possibilities of ferroelectric behavior of neural membranes, moving to the logical properties of neural pulses recognized as solitons, and finally exploring the architecture of cognition itself. It encourages invention via the methodical study of brain theory, including electrically reversible neurons, neural networks, associative memory systems within the brain, neural state machines within associative memory, and reversible computers in general. These models use standard analog and digital circuits that, in contrast to models that include non-physical components, may be applied directly toward the goal of constructing a machine with artificial intelligence based on patterns of the brain.

Writing from the circuits and systems perspective, the author reaches across specialized disciplines including neuroscience, psychology, and physics to achieve uncommon coverage of:

Neural membranes

Neural pulses and neural memory

Circuits and systems for memorizing and recalling

Dendritic processing and human learning

Artificial learning in artificial neural networks

The asset of reversibility in man and machine

Electrically reversible nanoprocessors

Reversible arithmetic

Hamiltonian circuit finders

Quantum versus classical

Each chapter introduces and develops new material and ends with exercises for readers to put their skills into practice. Appendices are provided for non-experts who want a quick overview of brain anatomy, brain psychology, and brain scanning. The nature of this book, with its summaries of major bodies of knowledge, makes it a most valuable reference for professionals, researchers, and students with career goals in artificial intelligence, intelligent systems, neural networks, computer architecture, and neuroscience.

A solutions manual is available for instructors; to obtain a copy please email the editorial department at ialine@wiley.com.

This book models  an idealized neuron as being driven by basic electrical elements, the goal being to systematically characterize the logical properties of neural pulses.  In order to constitute a system, neurons as pulsating devices may be represented using novel circuit elements as delineated in this book.  A plausible brain system is implied by the delineated elements and logically follows from known and likely properties of a neuron. New to electrical science are novel pulse-related circuit elements involving recursive neurons.  A recursive neuron, when properly excited, produces a self-sustaining pulse train that when sampled,  provides a true output with a specified probability, and a false output with complementary probability.  Because of its similarity to the qubits of quantum mechanics, the recursive pulsating neuron is termed a simulated qubit.  Recursive neurons easily function as controlled toggle devices and so are capable of massively parallel calculations, this being a new dimension in brain functioning as described in this book.   Simulated qubits and their possibilities are compared to the qubits of quantum physics.  Included in the book are suggested neural circuits for associative memory search via a randomized process of cue selection, and neural circuits for priority calculations.  These serve to select returns from long term memory, which in turn determines one's next conscious thought or action based on past memorized experiences. The book reports on proposals involving electron tunneling between synapses, and quantum computations within neurons.  Although not a textbook, there are easy exercises at the ends of chapters, and in the appendix there are twelve simulation experiments concerning neurons.​

This book models  an idealized neuron as being driven by basic electrical elements, the goal being to systematically characterize the logical properties of neural pulses.  In order to constitute a system, neurons as pulsating devices may be represented using novel circuit elements as delineated in this book.  A plausible brain system is implied by the delineated elements and logically follows from known and likely properties of a neuron. New to electrical science are novel pulse-related circuit elements involving recursive neurons.  A recursive neuron, when properly excited, produces a self-sustaining pulse train that when sampled,  provides a true output with a specified probability, and a false output with complementary probability.  Because of its similarity to the qubits of quantum mechanics, the recursive pulsating neuron is termed a simulated qubit.  Recursive neurons easily function as controlled toggle devices and so are capable of massively parallel calculations, this being a new dimension in brain functioning as described in this book.   Simulated qubits and their possibilities are compared to the qubits of quantum physics.  Included in the book are suggested neural circuits for associative memory search via a randomized process of cue selection, and neural circuits for priority calculations.  These serve to select returns from long term memory, which in turn determines one''s next conscious thought or action based on past memorized experiences. The book reports on proposals involving electron tunneling between synapses, and quantum computations within neurons.  Although not a textbook, there are easy exercises at the ends of chapters, and in the appendix there are twelve simulation experiments concerning neurons.​