Details

Autor(en) / Beteiligte

• Burger, John Robert,

Titel

Human memory modeled with standard analog and digital circuits : inspiration for man-made computers [electronic resource]

Auflage

1st edition

Link zum Volltext

• Wiley Online Library - AutoHoldings Books

Beschreibungen/Notizen

• Description based upon print version of record.
• Includes bibliographical references and index.
• HUMAN MEMORY MODELED WITH STANDARD ANALOG AND DIGITAL CIRCUITS; CONTENTS; PREFACE; 1 BRAIN BEHAVIOR POINTS THE WAY; Introduction; Modeling; Why Thinking Dissipates So Few Calories; The Miracle of Parallel Processing; Singularity; The Benefits of Reading This Book; Overview of the Book; Applications of the Models in the Book; Conclusions; Exercises; 2 NEURAL MEMBRANES AND ANIMAL ELECTRICITY; Introduction; The Physical Neuron; Ionic Solutions and Stray Electrons; Nernst Voltage; Ion-Channel Model; Applications; Conclusions; Exercises; 3 NEURAL PULSES AND NEURAL MEMORY; Introduction
• Derivation of a Neural Pulse Using Basic PhysicsNeuron Signal Propagation; Modeling Neurons as Adiabatic; Neurons for Memory; Applications; Conclusions; Exercises; Appendix: Asymptotically Adiabatic Circuits; 4 CIRCUITS AND SYSTEMS FOR MEMORIZATION AND RECALL; Introduction; Psychological Considerations When Modeling Human Memory; Basic Assumptions to Create a Model; Short-Term Memory and Consciousness; Cognitive Architecture; Discussion of the Model; Enabled Neural Logic; Models for Memorization; Applications; Conclusions; Exercises; 5 DENDRITIC PROCESSING AND HUMAN LEARNING; Introduction
• Biological Versus Artificial Neural NetworksDendrites; Neurons for Combinational Learning; Neurons for State-Machine Learning; Learning Circuits; Dendritic Processing Models; Enabled Logic Directly at the Soma; Comments on the Adiabatic Nature of Dendrites; Applications; Conclusions; Exercises; Appendix: Circuit Simulations of Neural Soliton Propagation; Conclusions; 6 ARTIFICIAL LEARNING IN ARTIFICIAL NEURAL NETWORKS; Introduction; Artificial Neurons; Artificial Learning Methods; Discussion of Learning Methods; Conclusion; Exercises; 7 THE ASSET OF REVERSIBILITY IN HUMANS AND MACHINES
• IntroductionSavants; Neural Models that Explain Savants; Parallel Processing and the Savant Brain; Computational Possibilities Using Conditional Toggle Memory; The Cost of Computation; Reversible Programming; Conclusions; Exercises; Appendix: Split-Level Charge Recovery Logic; 8 ELECTRICALLY REVERSIBLE NANOPROCESSORS; Introduction; A Gauge for Classical Parallelism; Design Rules for Electrical Reversibility; Reversible System Architecture; Architecture for Self-Analyzing Memory Words; Electrically Reversible Toggle Circuit; Reversible Addition Programming Example
• Reversible Subtraction Programming ExampleConclusions; Exercises; 9 MULTIPLICATION, DIVISION, AND HAMILTONIAN CIRCUITS; Introduction; Unsigned Multiplication; Restoring Division; Solving Hard Problems; Hamiltonian Circuits; The Initialization of Toggle Memory in Nanoprocessors; Logically Reversible Programming Using Nanobrains; Conclusions; Exercises; 10 QUANTUM VERSUS CLASSICAL COMPUTING; Introduction; Physical Qubits; Quantum Boolean Functions; Quantum Computer Programming; Historical Quantum Computing Algorithms; Conclusions; Exercises; APPENDIX A HUMAN BRAIN ANATOMY; Components of a Brain
• Forebrain Structure
• 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 me
• English