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Machine Intelligence and Signal Analysis

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Machine Intelligence and Signal Analysis Synopsis

The book covers the most recent developments in machine learning, signal analysis, and their applications. It covers the topics of machine intelligence such as: deep learning, soft computing approaches, support vector machines (SVMs), least square SVMs (LSSVMs) and their variants; and covers the topics of signal analysis such as: biomedical signals including electroencephalogram (EEG), magnetoencephalography (MEG), electrocardiogram (ECG) and electromyogram (EMG) as well as other signals such as speech signals, communication signals, vibration signals, image, and video. Further, it analyzes normal and abnormal categories of real-world signals, for example normal and epileptic EEG signals using numerous classification techniques. The book is envisioned for researchers and graduate students in Computer Science and Engineering, Electrical Engineering, Applied Mathematics, and Biomedical Signal Processing.

About This Edition

ISBN: 9789811309229
Publication date:
Author: M Tanveer, Ram Bilas Pachori
Publisher: Springer an imprint of Springer Nature Singapore
Format: Paperback
Pagination: 767 pages
Series: Advances in Intelligent Systems and Computing
Genres: Artificial intelligence
Digital signal processing (DSP)
Electrical engineering
Electronics engineering
Network hardware

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