Pattern Recognition and Machine Learning: Proceedings of the Japan-U.S. Seminar on the Learning Process in Control Systems, held in Nagoya, Japan August 18-20, 1970

Fu, King-Sun, editor

ISBN 10: 0306305461 / ISBN 13: 9780306305467

Edité par Plenum, 1971

A propos de cet article

344 pp., hardcover, ex library else text clean & binding tight (lacks dust jacket). - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country.

N° de réf. du vendeur ZB1194533

Détails bibliographiques

• Titre: Pattern Recognition and Machine Learning: Proceedings of the Japan-U.S. Seminar on the Learning Process in Control Systems, held in Nagoya, Japan August 18-20, 1970
• Éditeur: Plenum
• Date de parution: 1971
• Langue: anglais
• ISBN à 10 chiffres: 0306305461
• ISBN à 13 chiffres: 9780306305467
• Reliure: Couverture rigide
• État de l'article: Good

A propos de ce titre

Synopsis

This book contains the Proceedings of the US-Japan Seminar on Learning Process in Control Systems. The seminar, held in Nagoya, Japan, from August 18 to 20, 1970, was sponsored by the US-Japan Cooperative Science Program, jointly supported by the National Science Foundation and the Japan Society for the Promotion of Science. The full texts of all the presented papers except two t are included. The papers cover a great variety of topics related to learning processes and systems, ranging from pattern recognition to systems identification, from learning control to biological modelling. In order to reflect the actual content of the book, the present title was selected. All the twenty-eight papers are roughly divided into two parts--Pattern Recognition and System Identification and Learning Process and Learning Control. It is sometimes quite obvious that some papers can be classified into either part. The choice in these cases was strictly the editor's in order to keep a certain balance between the two parts. During the past decade there has been a considerable growth of interest in problems of pattern recognition and machine learn- ing. In designing an optimal pattern recognition or control system, if all the a priori information about the process under study is known and can be described deterministically, the optimal system is usually designed by deterministic optimization techniques.