Neuromorphic Systems Engineering: Neural Networks in Silicon: The Springer International Series in Engineering and Computer Science, cartea 447
Editat de Tor Sverre Landeen Limba Engleză Paperback – 6 mai 2013
Neuromorphic Systems Engineering: Neural Networks in Silicon provides the reader with a snapshot of neuromorphic engineering today. It is organized into five parts viewing state-of-the-art developments within neuromorphic engineering from different perspectives.
Neuromorphic Systems Engineering: Neural Networks in Silicon provides the first collection of neuromorphic systems descriptions with firm foundations in silicon. Topics presented include:
Neuromorphic Systems Engineering: Neural Networks in Silicon serves as an excellent resource for scientists, researchers and engineers in this emerging field, and may also be used as a text for advanced courses on the subject.
Toate formatele și edițiile | Preț | Express |
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Paperback (1) | 937.26 lei 6-8 săpt. | |
Springer Us – 6 mai 2013 | 937.26 lei 6-8 săpt. | |
Hardback (1) | 943.31 lei 6-8 săpt. | |
Springer Us – 30 apr 1998 | 943.31 lei 6-8 săpt. |
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Specificații
ISBN-13: 9781475782981
ISBN-10: 1475782985
Pagini: 484
Ilustrații: XVII, 462 p.
Dimensiuni: 155 x 235 x 25 mm
Greutate: 0.67 kg
Ediția:Softcover reprint of the original 1st ed. 1998
Editura: Springer Us
Colecția Springer
Seria The Springer International Series in Engineering and Computer Science
Locul publicării:New York, NY, United States
ISBN-10: 1475782985
Pagini: 484
Ilustrații: XVII, 462 p.
Dimensiuni: 155 x 235 x 25 mm
Greutate: 0.67 kg
Ediția:Softcover reprint of the original 1st ed. 1998
Editura: Springer Us
Colecția Springer
Seria The Springer International Series in Engineering and Computer Science
Locul publicării:New York, NY, United States
Public țintă
ResearchCuprins
Cochlear Systems.- Filter Cascades as Analogs of the Cochlea.- An Analogue VLSI Model of Active Cochlea.- A Low-Power Wide-Dynamic-Range Analog VLSI Cochlea.- Speech Recognition Experiments with Silicon Auditory Models.- Retinomorphic Systems.- The Retinomorphic Approach: Pixel-Parallel Adaptive Amplification, Filtering, and Quantization.- Analog VLSI Excitatory Feedback Circuits for Attentional Shifts and Tracking.- Floating-Gate Circuits for Adaptation of Saccadic Eye Movement Accuracy.- Neuromorphic Communication.- to Neuromorphic Communication.- A Pulsed Communication/Computation Framework for Analog VLSI Perceptive Systems.- Asynchronous Communication of 2D Motion Information Using Winner-Takes-All Arbitration.- Communicating Neuronal Ensembles between Neuromorphic Chips.- Neuromorphic Technology.- Introduction: From Neurobiology to Silicon.- A Low-Power Wide-Linear-Range Transconductance Amplifier.- Floating-Gate MOS Synapse Transistors.- Neuromorphic Synapses for Artificial Dendrites.- Winner-Take-All Networks with Lateral Excitation.- Neuromorphic Learning.- Neuromorphic Learning VLSI Systems: A Survey.- Analog VLSI Stochastic Perturbative Learning Architectures.- Winner-Takes-All Associative Memory: A Hamming Distance Vector Quantizer.