Machine Learning for Signal Processing - Data Science, Algorithms, and Computational Statistics

Describes the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most important and exciting technologies in the modern information economy. Builds up concepts gradually so that the ideas and algorithms can be implemented in practical software applications.

List of contents

• 1: Mathematical Foundations


• 2: Optimization


• 3: Random Sampling


• 4: Statistical Modelling and Inference


• 5: Probabalistic 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

About the author

Max A. Little is Professor of Mathematics at Aston University, UK, and a world-leading expert in signal processing and machine learning. His research in machine learning for digital health is highly influential and is the basis of advances in basic and applied research into quantifying neurological disorders such as Parkinson disease. He has published over 60 articles in the scientific literature on the topic, two patents, and a textbook. He is an advisor to government and leading international corporations in topics such as machine learning for health.

Summary

Describes the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most important and exciting technologies in the modern information economy. Builds up concepts gradually so that the ideas and algorithms can be implemented in practical software applications.

Product details

• Authors: Max A. Little, Prof Max A. (Professor of Mathematics Little
• Publisher: Oxford University Press
• Languages: English
• Product format: Paperback / Softback
• Released: 28.02.2024
• EAN: 9780198896555
• ISBN: 978-0-19-889655-5
• No. of pages: 384
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; machine learning, NON-CLASSIFIABLE, COMPUTERS / Computer Science, TECHNOLOGY & ENGINEERING / Signals & Signal Processing, TECHNOLOGY & ENGINEERING / Telecommunications, algorithms and data structures, Signal Processing, Algorithms & data structures, Statistical physics, COMPUTERS / Artificial Intelligence / General, Digital signal processing (DSP)