عنوان

Artificial Neural Networks

شابک

9781441951328

شابک

9781475745474

شماره

dltt

عنوان اصلي

Artificial Neural Networks

نام عام مواد

[Book]

ساير اطلاعات عنواني

Learning Algorithms, Performance Evaluation, and Applications /

نام نخستين پديدآور

by N. B. Karayiannis, A. N. Venetsanopoulos.

محل نشرو پخش و غیره

Boston, MA :

نام ناشر، پخش کننده و غيره

Imprint: Springer,

تاریخ نشرو بخش و غیره

1993.

عنوان فروست

Springer International Series in Engineering and Computer Science,

مشخصه جلد

209

شاپا ي ISSN فروست

0893-3405 ;

متن يادداشت

1 Introduction -- 2 Neural Network Architectures and Learning Schemes -- 3 ELEANNE: Efficient LEarning Algorithms for Neural NEtworks -- 4 Fast Learning Algorithms for Neural Networks -- 5 ALADIN: Algorithms for Learning and Architecture DetermlNation -- 6 Performance Evaluation of Single-layered Neural Networks -- 7 High-order Neural Networks and Networks with Composite Key Patterns -- 8 Applications of Neural Networks: A Case Study -- 9 Applications of Neural Networks: A Review -- 10 Future Trends and Directions -- References -- Author Index.

بدون عنوان

0

متن يادداشت

The recent interest in artificial neural networks has motivated the publication of numerous books, including selections of research papers and textbooks presenting the most popular neural architectures and learning schemes. Artificial Neural Networks: Learning Algorithms, Performance Evaluation, and Applications presents recent developments which can have a very significant impact on neural network research, in addition to the selective review of the existing vast literature on artificial neural networks. This book can be read in different ways, depending on the background, the specialization, and the ultimate goals of the reader. A specialist will find in this book well-defined and easily reproducible algorithms, along with the performance evaluation of various neural network architectures and training schemes. Artificial Neural Networks can also help a beginner interested in the development of neural network systems to build the necessary background in an organized and comprehensive way. The presentation of the material in this book is based on the belief that the successful application of neural networks to real-world problems depends strongly on the knowledge of their learning properties and performance. Neural networks are introduced as trainable devices which have the unique ability to generalize. The pioneering work on neural networks which appeared during the past decades is presented, together with the current developments in the field, through a comprehensive and unified review of the most popular neural network architectures and learning schemes. Efficient LEarning Algorithms for Neural NEtworks (ELEANNE), which can achieve much faster convergence than existing learning algorithms, are among the recent developments explored in this book. A new generalized criterion for the training of neural networks is presented, which leads to a variety of fast learning algorithms. Finally, Artificial Neural Networks presents the development of learning algorithms which determine the minimal architecture of multi-layered neural networks while performing their training. Artificial Neural Networks is a valuable source of information to all researchers and engineers interested in neural networks. The book may also be used as a text for an advanced course on the subject.

شماره استاندارد بين المللي کتاب و موسيقي

9781441951328

عنوان

Springer eBooks

موضوع مستند نشده

Computer engineering.

موضوع مستند نشده

Engineering.

موضوع مستند نشده

Systems engineering.

مستند نام اشخاص تاييد نشده

Karayiannis, N. B.

مستند نام اشخاص تاييد نشده

Venetsanopoulos, A. N.

مستند نام تنالگان تاييد نشده

SpringerLink (Online service)

تاريخ عمليات

20190301074200.0

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y