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Springer Radial Basis Function Networks 2: New Advances in Design

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Description

Radial Basis Function Networks 2 explores the latest advances in RBF network design and applications within the Studies in Fuzziness and Soft Computing series. This comprehensive volume from Springer examines enhanced training algorithms and architectural variations that improve RBF network performance for classification and functional approximation tasks. The book demonstrates why RBF networks have become increasingly popular, highlighting their rapid training capabilities compared to other neural-network techniques. Discover practical applications across robotics, biomedical engineering, and the financial sector, with in-depth coverage of how RBF networks serve as valuable tools for solving complex real-world problems. Ideal for researchers and practitioners seeking to understand modern RBF network methodologies and their implementation in diverse applications.

Key Features

Covers advanced training algorithms and architectural innovations in Radial Basis Function Networks for improved performance.

Explores RBF network applications across robotics, biomedical engineering, and financial sector industries.

Part of Springer's Studies in Fuzziness and Soft Computing series, volume 67, providing academic rigour and peer-reviewed research.

Demonstrates rapid training capabilities of RBF networks compared to traditional neural-network techniques.

Addresses functional approximation and classification applications with practical design guidance.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
27 March 2001
Listed Since
16 January 2007

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No barcode data available

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