Paperback. Zustand: new. Paperback. The text discusses recurrent neural networks for prediction and offers new insights into the learning algorithms, architectures, and stability of recurrent neural networks. It discusses important topics including recurrent and folding networks, long short-term memory (LSTM) networks, gated recurrent unit neural networks, language modeling, neural network model, activation function, feed-forward network, learning algorithm, neural turning machines, and approximation ability. The text discusses diverse applications in areas including air pollutant modeling and prediction, attractor discovery and chaos, ECG signal processing, and speech processing. Case studies are interspersed throughout the book for better understanding.FEATURES Covers computational analysis and understanding of natural languages Discusses applications of recurrent neural network in e-Healthcare Provides case studies in every chapter with respect to real-world scenarios Examines open issues with natural language, health care, multimedia (Audio/Video), transportation, stock market, and logisticsThe text is primarily written for undergraduate and graduate students, researchers, and industry professionals in the fields of electrical, electronics and communication, and computer engineering/information technology. This book comprehensively covers concepts of recurrent neural networks and discusses practical issues such as predictability and nonlinearity detecting. It will an ideal text for senior undergraduate, graduate students, researchers, and professionals in the fields of electrical, electronics and communication, and computer engineering. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verk�ufers 9781032310565

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Recurrent Neural Networks: Concepts and Applications

Kumar Tyagi, Amit (Editor)/ Abraham, Ajith (Editor)

Verlag: CRC Pr I Llc, 2024

ISBN 10: 1032310561 ISBN 13: 9781032310565

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Paperback. Zustand: Brand New. 412 pages. 9.18x6.12x9.21 inches. In Stock. This item is printed on demand. Bestandsnummer des Verk�ufers __1032310561

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Recurrent neural networks

Verlag: CRC Press, 2024

ISBN 10: 1032310561 ISBN 13: 9781032310565

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Zustand: New. xvi, 396 pages, illustrations some color First edition Recurrent neural networks (CRC Press : 2023) Includes bibliographical references and index. Bestandsnummer des Verk�ufers 26397563535

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