Last edited by Shaktitaur

Saturday, April 25, 2020 | History

3 edition of **New directions in neural networks** found in the catalog.

New directions in neural networks

Italian Workshop on Neural Nets (18th 2008 Vietri Sul Mare, Italy)

- 134 Want to read
- 32 Currently reading

Published
**2009** by IOS Press in Amsterdam, Washington, DC .

Written in English

- Neural networks (Computer science),
- Theorie,
- Congresses,
- Neuronale Netze

**Edition Notes**

Includes bibliographical references and index.

Statement | edited by Bruno Apolloni, Simone Bassis and Maria Marinaro |

Series | Frontiers in artificial intelligence and applications. Knowledge-based intelligent engineering systems -- v. 193 |

Contributions | Apolloni, Bruno, 1946-, Bassis, Simone, Marinaro, M. |

Classifications | |
---|---|

LC Classifications | QA76.87 .I85 2008 |

The Physical Object | |

Pagination | ix, 265 p. : |

Number of Pages | 265 |

ID Numbers | |

Open Library | OL24803375M |

ISBN 10 | 9781586039844 |

LC Control Number | 2009921089 |

OCLC/WorldCa | 313654129 |

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This book presents the outcome of this discussion. New Directions in Neural Networks is divided in two general subjects, ‘models’ and ‘applications’ and two specific ones, ‘economy and complexity’ and ‘remote sensing image processing’.

In New Directions in Statistical Signal Processing, leading researchers from both signal processing and neural computation present new work that aims to promote interaction between the two book's 14 chapters, almost evenly divided between signal processing and neural computation, begin with the brain and move on to communication Price: $ Volume 1 covers learning, attractor networks, and hierarchical networks (including back-propagation networks).

Volume 2 takes up temporal networks (including recurrent networks), self-organizing networks, higher-order networks, and such new directions in neural networks as fuzzy networks and evolutionary networks.5/5(1).

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In this book, we will demonstrate the neural networks in a variety of real-world tasks such as image recognition and data science. We examine current neural network technologies, including ReLU activation, stochastic gradient descent, cross-entropy, regularization, dropout, and.

Neural Networks for Control highlights key issues in learning control and identifiesresearch directions that could lead to practical solutions for control problems in criticalapplication domains.

It addresses general issues of neural network based control and neural networklearning with regard to specific problems of motion planning and control in robotics, and takes upapplication domains well. An introduction to Neural Networks Ben Krose Patrick van der Smagt. Eigh th edition No v em ber.

c The Univ ersit yof Amsterdam P ermission is gran ted to distribute single copies of this book for noncommercial use as long it is distributed a whole in its original form and the names of authors and new hardw are dev elopmen ts increased the File Size: 1MB.

Though mathematical ideas underpin the study of neural networks, the author presents the fundamentals without the full mathematical apparatus. All aspects of the field are tackled, including artificial neurons as models of their real counterparts; the geometry of network action in pattern space; gradient descent methods, including back-propagation; associative memory and Hopfield nets; and 4/5(8).

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