Academic Press Library in Signal Processing
Volume 1: Signal Processing Theory, Speech and Acoustic Processing, and Machine Learning
Edited by- Sergios Theodoridis, Department of Informatics and Telecommunications, University of Athens, Greece
Aimed at university researchers, post graduate students and R&D engineers in industry, this reference gives tutorial-based, comprehensive reviews of key topics and technologies of research in signal processing theory, speech and acoustic processing, and machine learning, giving an invaluable starting point to the area through the insight and understanding that they provide.
This edition is one of three with the two others entitled:
Statistical, Wireless, Array and Radar Signal Processing (ISBN 9780123965004)
Image, Video and Biomedical Signal Processing, and Hardware (ISBN 9780123965011)
Features of this book include:- Quick tutorial reviews of important and emerging topics of research in signal, speech, acoustic, image and video processing.
- Reference content on core principles, technologies, algorithms and applications
- Edited and contributed by leading figures in the field
- Comprehensive references to journal articles and other literature upon which to build further , more detailed knowledge
With this reference source you will
- Quickly grasp an area of research with which you are unfamiliar
- Understand the underlying principles of a topic
- How a topic relates to other areas and learn of the research issues yet to be resolved.
Audience
PhD students
Hardbound, 1000 Pages
Published: August 2013
Imprint: Academic Press
ISBN: 978-0-12-396502-8
Contents
1. Introduction: Signal Processing Theory
2. Continuous-Time Signals and Systems
3. Discrete-Time Signals and Systems
4. Random Signals and Stochastic Processes
5. Sampling and Quantization
6. Discrete Transforms
7. Digital Filter Structures and Implementations
8. Parametric Estimation
9. Multirate Signal Processing
10. Frames
11. Adaptive Filtering
12. Wavelets & Multiscale
13. Introduction: Audio Signal Processing
14. Music signal processing (including transcription, pitch tracking, beat tracking)
15. Audio coding
16. Introduction: Acoustic Signal Processing
17. Acoustic echo cancellation
18. Dereverberation (including acoustic channel estimation and inversion)
19. Sound Field Synthesis
20. Introduction: Speech Processing
21. Speech production modelling and speech analysis
22. Speech enhancement (including noise reduction, issues of quality and intelligibility)
23. Introduction: Machine Learning
24. Learning Theory
25. Neural Networks
26. Kernel Methods and SVMs
27. On-line learning
28. Probabilistic Graphical Models
29. Monte-Carlo methods (MCMC, Particle Filters)
30. Clustering (K-means, EM Algorithm)
31. Unsupervised learning and latent variable models (PCA, ICA, NMF, ...)
32. Semi-supervised learning
33. Information based learning
34. Model selection
35. Music Mining
