Emerging Capabilities and Applications of Artificial Higher Order Neural Networks

Zhang, Ming

ISBN 10: 1799835634 / ISBN 13: 9781799835639

Edité par Engineering Science Reference, 2021

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Détails bibliographiques

• Titre: Emerging Capabilities and Applications of Artificial Higher Order Neural Networks
• Éditeur: Engineering Science Reference
• Date de parution: 2021
• Langue: anglais
• ISBN à 10 chiffres: 1799835634
• ISBN à 13 chiffres: 9781799835639
• Reliure: Couverture rigide
• État de l'article: As New

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Synopsis

Artificial neural network research is one of the new directions for new generation computers. Current research suggests that open box artificial higher order neural networks (HONNs) play an important role in this new direction. HONNs will challenge traditional artificial neural network products and change the research methodology that people are currently using in control and recognition areas for the control signal generating, pattern recognition, nonlinear recognition, classification, and prediction. Since HONNs are open box models, they can be easily accepted and used by individuals working in information science, information technology, management, economics, and business fields. Emerging Capabilities and Applications of Artificial Higher Order Neural Networks contains innovative research on how to use HONNs in control and recognition areas and explains why HONNs can approximate any nonlinear data to any degree of accuracy, their ease of use, and how they can have better nonlinear data recognition accuracy than SAS nonlinear procedures. Featuring coverage on a broad range of topics such as nonlinear regression, pattern recognition, and data prediction, this book is ideally designed for data analysists, IT specialists, engineers, researchers, academics, students, and professionals working in the fields of economics, business, modeling, simulation, control, recognition, computer science, and engineering research.

À propos de l?auteur

Ming Zhang received his M.S. degree in Information Processing and Ph.D. degree in the area of Computer Vision from East China Normal University, Shanghai, China, in 1982 and 1989, respectively. He held Postdoctoral Fellowships in artificial neural networks with the Chinese Academy of the Sciences from 1989 to 1991, and the USA National Research Council from 1991 to 1992. He worked as a project manager on face recognition for airport security system and Ph.D. co-supervisor at the University of Wollongong, Australia from 1992 to 1994. In 1994, he joined Monash University, Australia as a lecturer in the Computer Science department. From 1995 to 2000, he was a lecturer and then a senior lecturer and Ph.D. supervisor at the University of Western Sydney, Australia. He also held Senior Research Associate Fellowship in artificial neural networks with the USA National Research Council from 1999 to 2000. From 2000, he has been working as an associate professor and then, from 2008, as a full professor at the Christopher Newport University, Virginia, USA. He has published more than 100 papers in the top international journals and international conferences in the areas of face recognition, weather forecasting, financial data simulation by using artificial neural networks and artificial higher order neural networks.