£118.34

Springer VLSI for Neural Networks and Artificial Intelligence

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Description

As neural network and artificial intelligence algorithms grow in complexity, the demand for high-speed computational power continues to rise. Conventional scalar processors, which are primarily designed for numeric and data manipulations, often struggle to meet the specific efficiency needs of modern AI applications. This book by Springer addresses the limitations of standard processors by exploring the unique requirements of neurocomputing and artificial intelligence. It examines the shift toward hardware that can handle non-programming, learning, symbolic manipulation, and knowledge representation. For students, researchers, and engineers working in computer architecture and microprocessors, this text provides essential insights into the specialized constraints and demands of AI hardware. It bridges the gap between traditional computing methods and the advanced VLSI techniques required to power the next generation of intelligent systems.

Key Features

Addresses the increasing complexity of neural network and artificial intelligence algorithms and their growing application needs.

Explores the limitations of conventional scalar processors regarding numeric and data manipulation efficiency.

Examines the specific computational requirements for neurocomputing, including non-programming and learning capabilities.

Covers artificial intelligence demands such as symbolic manipulation and knowledge representation.

Provides a technical look at the different constraints and demands faced by modern AI hardware design.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
30 September 1994
Listed Since
12 January 2007

Barcode

No barcode data available

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