Recurrent Neural Networks - Concepts and Applications (Hardcover)

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 logistics The 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.

General

Imprint:	Taylor & Francis
Country of origin:	United Kingdom
Release date:	July 2022
First published:	2023
Editors:	Amit Kumar Tyagi • Ajith Abraham
Dimensions:	234 x 156mm (L x W)
Format:	Hardcover
Pages:	396
ISBN-13:	978-1-03-208164-9
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > Neural networks Promotions
LSN:	1-03-208164-3
Barcode:	9781032081649

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