Cover Image

System and circuit design for biologically-inspired learning

"The objective of the book is to introduce and bring together well-known circuit design aspects, as well as to cover up-to-date outcomes of theoretical studies in decision-making, biologically-inspired, and artificial intelligent learning techniques"--Provided by publisher.

Bibliographic Details
Corporate Author: IGI Global.
Other Authors: Temel, Turgay, 1970-
Format: Electronic
Language:English
Published: Hershey, Pa. : IGI Global (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA), c2011.
Subjects:
Neural networks (Computer science)
Biologically-inspired computing.
Logic circuits.
Biologically-inspired learning and intelligent system modeling
Representation of neuro-information and knowledge
Recurrent neural networks
Self-organizing fuzzy neural network training
Neuromodeling and natural optimization
DCGA optimization techniques
Parallel hardware for artificial neural networks
Neural network circuits
Analog circuit design with fuzzy inference
Implantable neural decoders
Online Access:Chapter PDFs via platform:
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020 # # |a 9781609600204 (ebook) 
020 # # |z 9781609600181 (hardcover) 
020 # # |z 9781609600198 (pbk.) 
024 7 # |a 10.4018/978-1-60960-018-1  |2 doi 
035 # # |a (CaBNVSL)gtp00545415 
035 # # |a (OCoLC)707616576 
040 # # |a CaBNVSL  |c CaBNVSL  |d CaBNVSL 
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082 0 4 |a 006.3/2  |2 22 
245 0 0 |a System and circuit design for biologically-inspired learning  |c Turgay Temel, editor.  |h [electronic resource] / 
260 # # |a Hershey, Pa. :  |b IGI Global (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA),  |c c2011. 
300 # # |a electronic texts (348 p.) :  |b ill., digital files. 
504 # # |a Includes bibliographical references. 
505 0 # |a 1. Biologically-inspired learning and intelligent system modeling / Giovanna Morgavi -- 2. Representation of neuro-information and knowledge / Frank van der Velde -- 3. Learning / Frank van der Velde -- 4. Biologically-inspired learning / Turgay Temel -- 5. Optimality-oriented stabilization for recurrent neural networks / Ziqian Liu -- 6. Design of globally robust control for biologically-inspired noisy recurrent neural networks / Ziqian Liu -- 7. A biologically inspired evolving spiking neural model with rank-order population coding and a taste recognition system case study / S. Soltic, N. Kasabov -- 8. Faster self-organizing fuzzy neural network training and improved autonomy with time-delayed synapses for locally recurrent learning / Damien Coyle, Girijesh Prasad, Martin McGinnity -- 9. Biologically-inspired learning and intelligence / Turgay Temel -- 10. A biomimetic adaptive algorithm and micropower circuit architecture for implantable neural decoders / Benjamin Rapoport, Rahul Sarpeshkar -- 11. FPGA coprocessor for simulation of neural networks using compressed matrix storage / Jr̲g Bornschein -- 12. Neural network circuits for embedded sensors applications / N. Medrano, G. Zatorre, M. Sanz, B. Calvo, S. Celma -- 13. Parallel hardware for artificial neural networks using fixed floating point representation / Nadia Nedjah, Rodrigo Martins da Silva, Luiza Mourelle -- 
505 0 # |a 14. A novel DCGA optimization technique for guaranteed BIBO-stable frequency-response masking digital filters incorporating bilinear lossless discrete-integrator IIR interpolation sub-filters / Syed Bokhari, Behrouz Nowrouzian -- 15. Neuromodeling and natural optimization of nonlinear devices and circuits / Paulo Silva, Rossana Cruz, Adaildo D'Assunção. 
506 # # |a Restricted to subscribers or individual electronic text purchasers. 
520 3 # |a "The objective of the book is to introduce and bring together well-known circuit design aspects, as well as to cover up-to-date outcomes of theoretical studies in decision-making, biologically-inspired, and artificial intelligent learning techniques"--Provided by publisher. 
530 # # |a Also available in print. 
538 # # |a Mode of access: World Wide Web. 
588 # # |a Description based on title screen (IGI Global, viewed Dec. 17, 2010). 
650 # 0 |a Neural networks (Computer science) 
650 # 0 |a Biologically-inspired computing. 
650 # 0 |a Logic circuits. 
653 # # |a Biologically-inspired learning and intelligent system modeling 
653 # # |a Representation of neuro-information and knowledge 
653 # # |a Recurrent neural networks 
653 # # |a Self-organizing fuzzy neural network training 
653 # # |a Neuromodeling and natural optimization 
653 # # |a DCGA optimization techniques 
653 # # |a Parallel hardware for artificial neural networks 
653 # # |a Neural network circuits 
653 # # |a Analog circuit design with fuzzy inference 
653 # # |a Implantable neural decoders 
700 1 # |a Temel, Turgay,  |d 1970- 
710 2 # |a IGI Global. 
776 0 # |c (Original)  |w (DLC)2010017198 
776 0 8 |i Print version:  |w (DLC) 2010017198  |z 9781609600181  |z 1609600185 
856 4 1 |u https://ezaccess.library.uitm.edu.my/login?url=http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-60960-018-1  |3 Chapter PDFs via platform: 

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