Machine Intelligence and Signal Analysis

• Corporate Author: SpringerLink (Online service)
• Other Authors: Tanveer, M. (Editor, http://id.loc.gov/vocabulary/relators/edt), Pachori, Ram Bilas (Editor, http://id.loc.gov/vocabulary/relators/edt)
• Format: Electronic eBook
• Language: English
• Published: Singapore : Springer Singapore : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Series: Advances in Intelligent Systems and Computing, 748
• Subjects: Computational intelligence.; Signal processing.; Image processing.; Speech processing systems.; Computer communication systems.; Power electronics.; Computational Intelligence.; Signal, Image and Speech Processing.; Computer Communication Networks.; Power Electronics, Electrical Machines and Networks.
• Physical Description: XX, 767 p. 301 illus., 224 illus. in color. online resource.
• ISBN: 9789811309236
• ISSN: 2194-5357 ;
• DOI: 10.1007/978-981-13-0923-6

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.