Название: Machine Intelligence and Signal Analysis Автор: M. Tanveer, Ram Bilas Pachori Издательство: Springer Серия: Advances in Intelligent Systems and Computing (Book 748) Год: 2019 Страниц: 757 Язык: английский Формат: True PDF Размер: 28.5 MB
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.
Machine learning and signal processing are widely used approaches for solving real-world problems. Machine learning is a revolutionizing domain of public research which involves optimization and signal processing techniques. It is an interdisciplinary paradigm which covers a lot of areas of science and engineering.
In order to provide better solutions, advanced signal processing techniques with optimal machine learning solutions are required. In the recent years, the techniques related to signal processing and machine learning have been frequently used for biomedical applications.