Artificial Higher Order Neural Networks for Computer Science and Engineering: Trends for Emerging Applications

Artificial Higher Order Neural Networks for Computer Science and Engineering: Trends for Emerging Applications

Ming Zhang
Indexed In: SCOPUS
Release Date: February, 2010|Copyright: © 2010 |Pages: 660
DOI: 10.4018/978-1-61520-711-4
ISBN13: 9781615207114|ISBN10: 1615207112|EISBN13: 9781615207121
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Description & Coverage
Description:

Artificial neural network research is one of the promising new directions for the next generation of computers and open box artificial Higher Order Neural Networks (HONNs) play an important role in this future.

Artificial Higher Order Neural Networks for Computer Science and Engineering: Trends for Emerging Applications introduces Higher Order Neural Networks (HONNs) to computer scientists and computer engineers as an open box neural networks tool when compared to traditional artificial neural networks. Since HONNs are open box models, they can be easily used in information science, information technology, management, economics, and business. This book details the techniques, theory and applications essential to engaging and capitalizing on this developing technology.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Artificial Higher Order Neural Networks for Computer Engineering
  • Artificial Tactile Sensing and Robotic Surgery
  • Evolutionary Algorithms
  • Hardware Implementations of First and Higher Order Neural Networks
  • Higher Order Neural Network Models for Data Mining
  • Higher Order Neural Networks
  • Neural Network Theory and Applications
  • Neuro – Fuzzy Control Schemes and Systems
  • Ordinary Neural Networks vs. Higher Order Neural Networks
  • Simulation and Modeling
Reviews & Statements

This is the first book which introduces Higher Order Neural Networks (HONNs) to people working in the fields of computer science and computer engineering, and presents to them that HONNs is an open box neural networks tool compare to traditional artificial neural networks. This is the first book which includes details of the most popular HONNs models and provides opportunities for millions of people working in the computer science and computer engineering areas to know what HONNs are, and how to use HONNs in computer science and computer engineering areas.

– Ming Zhang, Christopher Newport University, USA
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Editor/Author Biographies
Ming Zhang was born in Shanghai, China. He received the MS degree in information processing and PhD degree in the research 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 in 1989 and the USA National Research Council in 1991. He was a face recognition airport security system project manager and PhD co-supervisor at the University of Wollongong, Australia in 1992. Since 1994, he was a lecturer at the Monash University, Australia, with a research area of artificial neural network financial information system. From 1995 to 1999, he was a senior lecturer and PhD supervisor at the University of Western Sydney, Australia, with the research interest of artificial neural networks. He also held Senior Research Associate Fellowship in artificial neural networks with the USA National Research Council in 1999. He is currently a Full Professor and graduate student supervisor in computer science at the Christopher Newport University, VA, USA. With more than 100 papers published, his current research includes artificial neural network models for face recognition, weather forecasting, financial data simulation, and management.
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