Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Neural Networks and Learning Machines
Third Edition
Simon Haykin
McMaster University, Canada
This third edition of a classic book presents a comprehensive treatment of neural networks and learning machines. These two pillars that are closely related. The book has been revised extensively to provide an up-to-date treatment of a subject that is continually growing in importance. Distinctive features of the book include:
· On-line learning algorithms rooted in stochastic gradient descent; small-scale and large-scale learning problems.
· Kernel methods, including support vector machines, and the representer theorem.
· Information-theoretic learning models, including copulas, independent components analysis (ICA), coherent ICA, and information bottleneck.
· Stochastic dynamic programming, including approximate and neurodynamic procedures.
· Sequential state-estimation algorithms, including Kalman and particle filters.
· Recurrent neural networks trained using sequential-state estimation algorithms.
· Insightful computer-oriented experiments.
Just as importantly, the book is written in a readable style that is Simon Haykin’s hallmark.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Spese di spedizione:
EUR 32,00
Da: Spagna a: U.S.A.
Descrizione libro Condizione: Muy Bueno / Very Good. Codice articolo 100000000838894
Descrizione libro Condizione: Muy Bueno / Very Good. Codice articolo 100000000324079