- eBook:Machine Learning for Signal Processing: Data Science, Algorithms, and Computational Statistics
- Author:Max A. Little
- Data:October 13, 2019
- Pages:384 pages
Digital signal processing (DSP) is one of the 'foundational' engineering topics of the modern world, without which technologies such the mobile phone, television, CD and MP3 players, WiFi and radar, would not be possible. A relative newcomer by comparison, statistical machine learning is the theoretical backbone of exciting technologies such as automatic techniques for car registration plate recognition, speech recognition, stock market prediction, defect detection on assembly lines, robot guidance, and autonomous car navigation. Statistical machine learning exploits the analogy between intelligent information processing in biological brains and sophisticated statistical modelling and inference.
DSP and statistical machine learning are of such wide importance to the knowledge economy that both have undergone rapid changes and seen radical improvements in scope and applicability. Both make use of key topics in applied mathematics such as probability and statistics, algebra, calculus, graphs and networks. Intimate formal links between the two subjects exist and because of this many overlaps exist between the two subjects that can be exploited to produce new DSP tools of surprising utility, highly suited to the contemporary world of pervasive digital sensors and high-powered, yet cheap, computing hardware. This book gives a solid mathematical foundation to, and details the key concepts and algorithms in this important topic.
3. Random sampling
4. Statistical modelling and inference
5. Probabilistic graphical models
6. Statistical machine learning
7. Linear-Gaussian systems and signal processing
8. Discrete signals: sampling, quantization and coding
9. Nonlinear and non-Gaussian signal processing
10. Nonparametric Bayesian machine learning and signal processing
Download Machine Learning for Signal Processing: Data Science, Algorithms, and Computational Statistics PDF or ePUB format free