Cappy, Alain,  1954- <br/><br/>
Neuro-inspired information processing / 
Alain Cappy. 
 - 1 online resource (245 pages) :  illustrations. 
 - Electronic engineering series .
 - Electronics engineering series (London, England) .
<br/><br/>Includes bibliographical references and index. 
<br/><br/>Cover -- Half-Title Page -- Dedication -- Title Page -- Copyright Page -- Contents -- Acknowledgments -- Introduction -- 1. Information Processing -- 1.1. Background -- 1.1.1. Encoding -- 1.1.2. Memorization -- 1.2. Information processing machines -- 1.2.1. The Turing machine -- 1.2.2. von Neumann architecture -- 1.2.3. CMOS technology -- 1.2.4. Evolution in microprocessor performance -- 1.3. Information and energy -- 1.3.1. Power and energy dissipated in CMOS gates and circuits -- 1.4. Technologies of the future -- 1.4.1. Evolution of the "binary coding/von Neumann/CMOS" system 1.4.2. Revolutionary approaches -- 1.5. Microprocessors and the brain -- 1.5.1. Physical parameters -- 1.5.2. Information processing -- 1.5.3. Memorization of information -- 1.6. Conclusion -- 2. Information Processing in the Living -- 2.1. The brain at a glance -- 2.1.1. Brain functions -- 2.1.2. Brain anatomy -- 2.2. Cortex -- 2.2.1. Structure -- 2.2.2. Hierarchical organization of the cortex -- 2.2.3. Cortical columns -- 2.2.4. Intra- and intercolumnar connections -- 2.3. An emblematic example: the visual cortex -- 2.3.1. Eye and retina -- 2.3.2. Optic nerve -- 2.3.3. Cortex V1 2.3.4. Higher level visual areas V2, V3, V4, V5 and IT -- 2.3.5. Conclusion -- 2.4. Conclusion -- 3. Neurons and Synapses -- 3.1. Background -- 3.1.1. Neuron -- 3.1.2. Synapses -- 3.2. Cell membrane -- 3.2.1. Membrane structure -- 3.2.2. Intra- and extracellular media -- 3.2.3. Transmembrane proteins -- 3.3. Membrane at equilibrium -- 3.3.1. Resting potential, Vr -- 3.4. The membrane in dynamic state -- 3.4.1. The Hodgkin-Huxley model -- 3.4.2. Beyond the Hodgkin-Huxley model -- 3.4.3. Simplified HH models -- 3.4.4. Application of membrane models -- 3.5. Synapses 3.5.1. Biological characteristics -- 3.5.2. Synaptic plasticity -- 3.6. Conclusion -- 4. Artificial Neural Networks -- 4.1. Software neural networks -- 4.1.1. Neuron and synapse models -- 4.1.2. Artificial Neural Networks -- 4.1.3. Learning -- 4.1.4. Conclusion -- 4.2. Hardware neural networks -- 4.2.1. Comparison of the physics of biological systems and semiconductors -- 4.2.2. Circuits simulating the neuron -- 4.2.3. Circuits simulating the synapse -- 4.2.4. Circuits for learning -- 4.2.5. Examples of hardware neural networks -- 4.3. Conclusion -- References -- Index Other titles from iSTE in Electronics Engineering -- EULA 
<br/><br/><label>ISBN: </label>9781119721802 1119721806 9781119721796 1119721792 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Neural networks (Computer science)<br/>Neural computers.<br/>Neural computers.
<br/><br/><label>Index Terms--Genre/Form: </label><br/>Electronic books.
<br/><br/><label>LC Class. No.: </label>QA76.87  / .C37 2020 
<br/><br/><label>Dewey Class. No.: </label>006.3/2