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Adaptive Resonance Theory Microchips by Gotarredona | Springer | Neural Networks & Artificial Intelligence Research Book | ISBN 9780792382317

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Product Specifications

Specification Details
Title Adaptive Resonance Theory Microchips
Author Gotarredona
Publisher Springer
ISBN-13 9780792382317
ISBN-10 0792382315
Language English
Format Academic / Research Book
Subject Artificial Intelligence / Neural Networks
Key Topics Adaptive Resonance Theory, Neural Networks, Microchips, Neural Computation
Research Areas Artificial Intelligence, Pattern Recognition, Neuromorphic Engineering, VLSI
Academic Level Advanced / Postgraduate / Research
Book Type Scientific / Academic Reference
Target Audience Researchers, Engineers, Computer Scientists, Faculty, Postgraduate Students
Brand / Publisher Springer
ISBN/EAN 9780792382317

Short Description

Adaptive Resonance Theory Microchips explores hardware implementations of Adaptive Resonance Theory for neural computation, pattern recognition, learning systems, and intelligent information processing, making it a valuable reference for researchers and advanced students in artificial intelligence and neural networks.

Description

Adaptive Resonance Theory Microchips presents an advanced exploration of hardware-oriented approaches to Adaptive Resonance Theory (ART) and neural computation.

 

Adaptive Resonance Theory provides a framework for learning, categorization, pattern recognition, and stable neural processing. Implementing ART concepts in specialized microchip hardware offers opportunities for high-speed and efficient intelligent information processing.

 

This academic reference is particularly relevant to the study of neural networks, artificial intelligence, neuromorphic engineering, pattern recognition, machine learning, adaptive systems, VLSI technology, and intelligent hardware.

 

The book is suitable for researchers, electrical and electronics engineers, computer scientists, postgraduate students, university faculty, and professionals working with neural computation and hardware implementations of intelligent systems.

 

Key Features

 

• Focuses on Adaptive Resonance Theory hardware implementations

• Explores ART-based neural computation

• Relevant to neural networks and artificial intelligence

• Covers concepts related to intelligent hardware and microchips

• Useful for pattern recognition and machine learning research

• Relevant to neuromorphic and VLSI-based computing

• Suitable for advanced academic and research applications

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