Deep learning in time series analysis. (2023)

• Record Type: Book
• Further Information: Note: Arash Gharehbaghi.
• Authors: Gharehbaghi, Arash, 1972-
• Contents: PREFACE. I-FUNDAMENTALS OF LEARNING. Introduction to Learning. Learning Theory. Pre-processing and Visualisation. II ESSENTIALS OF TIME SERIES ANALYSIS. Basics of Time Series. Multi-Layer Perceptron (MLP) Neural Networks for Time Series Classification. Dynamic Models for Sequential Data Analysis. III DEEP LEARNING APPROACHES TO TIME SERIES CLASSIFICATION. Clustering for Learning at Deep Level. Deep Time Growing Neural Network. Deep Learning of Cyclic Time Series. Hybrid Method for Cyclic Time Series. Recurrent Neural Networks (RNN). Convolutional Neural Networks. Bibliography.
• Edition: 1st
• Publisher Details: Boca Raton : CRC Press
• Publication Date: 2023
• Extent: 1 online resource (196 pages), illustrations (black and white, and colour)
• Subjects: 006.310151955; Time-series analysis -- Data processing; Deep learning (Machine learning)
• Languages: English
• ISBNs: 9781000911435; 9781000911404
• Related ISBNs: 9780367321789
• Notes: Note: Includes bibliographical references and index.; Note: Description based on CIP data; resource not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.