Joy Iong-Zong Chen (ed.); João Manuel R. S. Tavares (ed.); Abdullah M. Iliyasu (ed.); Ke-Lin Du (ed.) Springer (2021) Saatavuus: Tilaustuote Pehmeäkantinen kirja
G. Rajakumar; Ke-Lin Du; Chandrasekar Vuppalapati; Grigorios N. Beligiannis Springer Verlag, Singapore (2022) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Springer Sivumäärä: 566 sivua Asu: Kovakantinen kirja Painos: 2006 Julkaisuvuosi: 2006, 18.04.2006 (lisätietoa) Kieli: Englanti
Conventional model-based data processing methods are computationally expensive and require experts’ knowledge for the modelling of a system. Neural networks are a model-free, adaptive, parallel-processing solution. This textbook provides a powerful and universal paradigm for information processing; it reviews the most popular neural-network methods and their associated techniques.
Each chapter has a systematic survey of each neural-network model. Computational intelligence topics like fuzzy logic and genetic algorithms (tools for neural-network learning) are introduced. Array signal processing problems are used to show the applications of each model.
This is an ideal textbook for graduate students and researchers; as well as introducing the basics, the exhaustive list of references included will aid their future research. It is also a valuable reference for scientists and practitioners working in pattern recognition, signal processing, speech and image processing, data analysis and A.I.
