| Description |
1 online resource (pages): illustrations |
| Contents |
Part I: Realms of Signal Processing: 1: Digital Signal Representation. 2: Signal Processing Background. 3: Fundamentals of Signal Transformation. 4: Digital Filters. 5: Estimation and Detection. 6: Adaptive Signal Processing. 7: Spectral Analysis -- Part II: Machine Learning and Recognition: 8: General Learning. 9: Signal Processes, Learning, and Recognition. 10: Stochastic Processes. 11: Feature Extraction. 12: Unsupervised Learning. 14: Fuzzy Logic and Rough Sets. 15: Neural Networks -- Part III: Real Aspects and Applications: 16: Noisy Signals. 17: Reasoning Methods and Noise Removal. 18: Audio Signals and Speech Recognition. 19: Noisy Speech. 20: Aspects of Human Hearing. 21: Speech Features. 22: Hidden Stochastic Model for Speech. 23: Different Speech Applications -- Part A. 24: Different Speech Applications -- Part B. 25: Biomedical Signals: ECG, EEG. 26: Seismic Signals. 27: Radar Signals. 28: Visual Story Telling. 29: Digital Processes and Multimedia. 30: Visualizations for Emergency Operation Centre. 31: Intelligent Interactive Communications. 32: Comparisons |
| Summary |
Signal processing captures, interprets, describes and manipulates physical phenomena. Mathematics, statistics, probability, and stochastic processes are among the signal processing languages we use to interpret real-world phenomena, model them, and extract useful information. This book presents different kinds of signals humans use and applies them for human machine interaction to communicate. Signal Processing and Machine Learning with Applications presents methods that are used to perform various Machine Learning and Artificial Intelligence tasks in conjunction with their applications. It is organized in three parts: Realms of Signal Processing; Machine Learning and Recognition; and Advanced Applications and Artificial Intelligence. The comprehensive coverage is accompanied by numerous examples, questions with solutions, with historical notes. The book is intended for advanced undergraduate and postgraduate students, researchers and practitioners who are engaged with signal processing, machine learning and the applications. |
| Subject |
Signal processing -- Digital techniques.
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Machine learning.
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Application software.
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Application software
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Machine learning
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Signal processing -- Digital techniques
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| Form |
Electronic book
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| Author |
Paul, Sheuli, author
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Kepuska, Veton, author
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Silaghi, Marius, author
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| ISBN |
9783319453729 |
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3319453726 |
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9788331945375 |
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8331945379 |
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