Recurrent Neural Networks: Concepts and Applications

Synopsis

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.

Copyright:

2022

Book Details

Book Quality:

Publisher Quality

Book Size:

396 Pages

ISBN-13:

9781000626179

Related ISBNs:

9781032081649, 9781003307822, 9781032310565

Publisher:

CRC Press

Date of Addition:

08/08/22

Copyrighted By:

selection and editorial matter, Amit Kumar Tyagi and Ajith Abraham

Adult content:

No

Language:

English

Has Image Descriptions:

No

Categories:

Nonfiction, Computers and Internet, Technology

Submitted By:

Bookshare Staff

Usage Restrictions:

This is a copyrighted book.

Edited by:

Amit Kumar Tyagi

Edited by:

Ajith Abraham