Neural Network Perception for Mobile Robot Guidance, Dean A. Pomerleau
Автор: A. Ravishankar Rao; Guillermo A. Cecchi Название: The Relevance of the Time Domain to Neural Network Models ISBN: 1461429927 ISBN-13(EAN): 9781461429920 Издательство: Springer Рейтинг: Цена: 26120.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Here is a unified view of how the time domain can be effectively employed in neural network models. Covers synchronization, phase-locking behavior, image processing, temporal pattern analysis, fMRI analyis, network topology and synchronizability and more.
Автор: Heidar A. Talebi; Farzaneh Abdollahi; Rajni V. Pat Название: Neural Network-Based State Estimation of Nonlinear Systems ISBN: 1441914374 ISBN-13(EAN): 9781441914378 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This text offers neural network schemes for state estimation, system identification and fault detection. It covers mathematical proof of stability, experimental evaluation, and robustness against unmolded dynamics, external disturbances and measurement noises.
Автор: Dean A. Pomerleau Название: Neural Network Perception for Mobile Robot Guidance ISBN: 0792393732 ISBN-13(EAN): 9780792393733 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Vision-based mobile robot guidance has proved difficult for classical machine vision methods because of the diversity and real-time constraints inherent in the task. This book describes a connectionist system called ALVINN (Autonomous Land Vehicle In a Neural Network) that overcomes these difficulties.
Автор: Martin A. Giese Название: Dynamic Neural Field Theory for Motion Perception ISBN: 1461375533 ISBN-13(EAN): 9781461375531 Издательство: Springer Рейтинг: Цена: 16979.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Dynamic Neural Field Theory for Motion Perception provides a new theoretical framework that permits a systematic analysis of the dynamic properties of motion perception. The author demonstrates how neural fields can be applied for the analysis of perceptual phenomena and its underlying neural processes.
Автор: Eduardo Montijano; Carlos Sag??s Название: Distributed Consensus with Visual Perception in Multi-Robot Systems ISBN: 3319156985 ISBN-13(EAN): 9783319156989 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Distributed Consensus with Visual Perception in Multi-Robot Systems
Автор: Arun K. Sood; Harry Wechsler Название: Active Perception and Robot Vision ISBN: 3642772277 ISBN-13(EAN): 9783642772276 Издательство: Springer Рейтинг: Цена: 14673.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Proceedings of the NATO Advanced Study Institute on Active Perception and Robot Vision, held at Maratea, Italy, July 16-29, 1989
Автор: Zhigang Zeng; Jun Wang Название: Advances in Neural Network Research and Applications ISBN: 3642129897 ISBN-13(EAN): 9783642129896 Издательство: Springer Рейтинг: Цена: 39182.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Including contributions from the world`s leading researchers in the field, this volume is made up of top-quality peer-reviewed papers that were some of the submissions to the seventh International Symposium on Neural Networks, held in China in 2010.
Автор: Daniel Vasquez; Rainer Gruhn; Wolfgang Minker Название: Hierarchical Neural Network Structures for Phoneme Recognition ISBN: 3642344240 ISBN-13(EAN): 9783642344244 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The subject of this study is the role of hierarchical structures, based on neural networks, in identifying phonemes in automated speech recognition systems. It shows how the artificial neural network paradigm can simplify the analysis of spoken language.
Описание: This book introduces concrete design methods and MATLAB simulations of stable adaptive Radial Basis Function (RBF) neural control strategies. It presents a broad range of implementable neural network control design methods for mechanical systems.
Описание: Introduction.- Designing of dynamic neural networks.- Estimation methods in training of ANNs for robust fault diagnosis.- MLP in robust fault detection of static non-linear systems.- GMDH networks in robust fault detection of dynamic non-linear systems.- State-space GMDH networks for actuator robust FDI.
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