Processing ......
FreeComputerBooks.com
Links to Free Computer, Mathematics, Technical Books all over the World
 
Artificial Neural Networks - Architectures and Applications
🌠 Top Free JavaScript Books - 100% Free or Open Source!
  • Title Artificial Neural Networks - Architectures and Applications
  • Author(s) Kenji Suzuki
  • Publisher: IN-TECH (January 16, 2013)
  • License(s): Attribution 3.0 Unported (CC BY 3.0)
  • Hardcover 264 pages
  • eBook PDF files
  • Language: English
  • ISBN-10: N/A
  • ISBN-13: 978-953-51-0935-8
  • Share This:  

Book Description

Artificial Neural Networks (ANN) may probably be the single most successful technology in the last two decades which has been widely used in a large variety of applications. The purpose of this book is to provide recent advances of architectures, methodologies, and applications of artificial neural networks.

The book consists of two parts: the architecture part covers architectures, design, optimization, and analysis of artificial neural networks; the applications part covers applications of artificial neural networks in a wide range of areas including biomedical, industrial, physics, and financial applications. Thus, this book will be a fundamental source of recent advances and applications of artificial neural networks. The target audience of this book includes college and graduate students, and engineers in companies.

About the Authors
  • Kenji Suzuki received his Ph.D. degree in information engineering from Nagoya University in 2001. From 1993 to 2001, he worked at Hitachi Medical Corporation, and then Aichi Prefectural University as faculty.
Reviews, Ratings, and Recommendations: Related Book Categories: Read and Download Links: Similar Books:
  • Neural Network Learning: Theoretical Foundations

    This book describes recent theoretical advances in the study of artificial neural networks. It explores probabilistic models of supervised learning problems, and addresses the key statistical and computational questions.

  • Introduction to Artificial Neural Networks (Jan Larsen, et al.)

    This fundamental book on Artificial Neural Networks (ANN) has its emphasis on clear concepts, ease of understanding and simple examples. It presents a large variety of standard neural networks with architecture, algorithms and applications.

  • Machine Learning with Neural Networks (Bernhard Mehlig)

    This modern and self-contained book offers a clear and accessible introduction to the important topic of machine learning with neural networks. It provides comprehensive coverage of neural networks, their evolution, their structure, their applications, etc.

  • Neural Network Design (Martin T. Hagan)

    This book provides a clear and detailed coverage of fundamental neural network architectures and learning rules. It emphasizes a coherent presentation of the principal neural networks, methods for training them and their applications to practical problems.

  • Applied Artificial Neural Networks (Christian Dawson)

    This book focuses on the application of neural networks to a diverse range of fields and problems. It collates contributions concerning neural network applications in areas such as engineering, hydrology and medicine.

  • Neural Networks - A Systematic Introduction (Raul Rojas)

    In this book, theoretical laws and models previously scattered in the literature are brought together into a general theory of artificial neural nets. It is aimed at readers who seek an overview of the field or who wish to deepen their knowledge.

  • An Introduction to Neural Networks (Kevin Gurney)

    With an easy to understand format using graphical illustrations and multidisciplinary scientific context, this book fills the gap in the market for neural networks for multi-dimensional scientific data, and relates neural networks to statistics.

  • Artificial Neural Networks - Methodological Advances and Apps

    The book begins with fundamentals of artificial neural networks, which cover an introduction, design, and optimization. Advanced architectures for biomedical applications, which offer improved performance and desirable properties, follow.

  • Recurrent Neural Networks and Soft Computing (M. ElHefnawi)

    Advanced information regarding the theory, concepts and applications of recurrent neural networks and the field of soft computing has been highlighted in this elaborative book. Additional topics in this vein are the application of AI techniques to electromagnetic interference problems, etc.

  • Recurrent Neural Networks for Temporal Data Processing

    By presenting the latest research work the book demonstrates how real-time recurrent neural networks (RNNs) can be implemented to expand the range of traditional signal processing techniques and to help combat the problem of prediction.

  • A Brief Introduction to Neural Networks (David Kriesel)

    Introduces the Java programmer to the world of Neural Networks and Artificial Intelligence using SNIPE. Examples include the traveling salesman problem, handwriting recognition, financial prediction, game strategy, mathematical functions, and Internet bots.

  • C++ Neural Networks and Fuzzy Logic (Valluru B. Rao, et al)

    Provides a logical and easy-to-follow progression through C++ programming for two of the most popular technologies for artificial intelligence: neural and fuzzy programming. Covers theory as well as practical working examples with reusable code.

Book Categories
:
Other Categories
Resources and Links