Artificial Neural Systems: Principle and Practice
(eBook)

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Published
Bentham Science Publishers, 2015.
Status
Available Online

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Format
eBook
Language
English
ISBN
9781681080901

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Citations

APA Citation, 7th Edition (style guide)

Pierre Lorrentz., & Pierre Lorrentz|AUTHOR. (2015). Artificial Neural Systems: Principle and Practice . Bentham Science Publishers.

Chicago / Turabian - Author Date Citation, 17th Edition (style guide)

Pierre Lorrentz and Pierre Lorrentz|AUTHOR. 2015. Artificial Neural Systems: Principle and Practice. Bentham Science Publishers.

Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)

Pierre Lorrentz and Pierre Lorrentz|AUTHOR. Artificial Neural Systems: Principle and Practice Bentham Science Publishers, 2015.

MLA Citation, 9th Edition (style guide)

Pierre Lorrentz, and Pierre Lorrentz|AUTHOR. Artificial Neural Systems: Principle and Practice Bentham Science Publishers, 2015.

Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.

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Grouped Work IDa5a3edc0-c3c6-f874-6feb-36a6f06c7a5e-eng
Full titleartificial neural systems principle and practice
Authorlorrentz pierre
Grouping Categorybook
Last Update2023-10-03 20:03:37PM
Last Indexed2024-04-18 01:54:05AM

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First LoadedNov 7, 2022
Last UsedDec 17, 2023

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    [synopsis] => An intelligent system is one which exhibits characteristics including, but not limited to, learning, adaptation, and problem-solving. Artificial Neural Network (ANN) Systems are intelligent systems designed on the basis of statistical models of learning that mimic biological systems such as the human central nervous system. Such ANN systems represent the theme of this book. This book also describes concepts related to evolutionary methods, clustering algorithms, and others networks which are complementary to ANN system. The book is divided into two parts. The first part explains basic concepts derived from the natural biological neuron and introduces purely scientific frameworks used to develop a viable ANN model. The second part expands over to the design, analysis, performance assessment, and testing of ANN models. Concepts such as Bayesian networks, multi-classifiers, and neuromorphic ANN systems are explained, among others.

Artificial Neural Systems: Principles and Practice takes a developmental perspective on the subject of ANN systems, making it a beneficial resource for students undertaking graduate courses and research projects, and working professionals (engineers, software developers) in the field of intelligent systems design.
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