Synopsis
The term neural networks is used to describe a number of different models intended to imitate some of the functions of the human brain, using certain of its basic structures. The authors aim to convey an intuitive and practical understanding of the topic and to provide the foundations necessary before undertaking further study. To this end, the first part of the book is devoted to a description of biological foundations. Biology is the source of study of neural networks and it seems probable that it will continue to provide a source of essential ideas. Following this introduction, a general model for neural networks is presented and a number of today's most important models are studied. Lastly, a number of real applications are discussed.
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About the Author
LAURENT CONDAMIN is engineer of the French Grande Ecole "Ecole Centrale de Paris," PhD in Applied Mathematics and Associate in Risk Management (Insurance Institute of America). He is currently partner and managing director of Elseware where he makes consultancy on risk modelling in top leading companies.
JEAN-PAUL LOUISOT is a civil engineer, Master in Economics, Master in Business Administration (Kellog, 1972) and Associate in Risk Management. He has spent more than thirty years of his career to service private and public entities helping them manage their risks and coach their risk managers and executives. As director for the CARM_institute, Ltd, he is in charge of the professional designations ARM and EFARM. As a Professor at Pantheon/Sorbonne University, he teaches a postgraduate course in Risk Management. Jean-Paul teaches also in various Engineering Schools and MBA programs. Previous publications include "Exposure Diagnostic" (AFNOR - 2004) and "100 Questions to understand Risk Management" (AFNOR - 2005).
PATRICK NAIM graduated from Ecole Centrale de Paris, and Associate in Risk Management (ARM). He is the founder and CEO of Elseware, a consulting company specialising in quantitative modelling and risk quantification. He also teaches data modelling and Bayesian Networks in several universities and engineering schools in France. He is author of several books in the field of quantitative modelling.
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Neural Networks
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Macmillan Education, Limited, 1991
ISBN 10: 0333549961
ISBN 13: 9780333549964
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