Machine Intelligence and Signal Analysis
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Beschreibung
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.
Presents the latest advances in the area of data mining, artificial intelligence, optimization, machine learning methods and algorithms Discusses applications for studying human brain and heart disorders like epilepsy, Alzheimer’s, and coronary artery disease Serves as a valuable reference resource for future work
Autor*in
M. Tanveer
Themen in »Machine Intelligence and Signal Analysis«
Signal Processing Machine Learning Conference Proceedings MISP Early Diagnosis of Alzheimer disease Detection of Sleep Related Disorders Time-frequency Analysis Kernel Design