Actions for Machine learning for signal processing [electronic resource] : data science, algorithms, and computational statistics

Email RIS file
Bookmark
Report an Issue

Machine learning for signal processing [electronic resource] : data science, algorithms, and computational statistics / Max A. Little

Author
Little, Max A.
Published
New York, NY : Oxford University Press, 2019.
Edition
First edition.
Physical Description
xviii, 359 pages : illustrations (some color) ; 26 cm
Access Online

Availability

I Want It
I Want It

Finding items...

Restrictions on Access
License restrictions may limit access.
Summary
"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 and yet cheap, computing hardware. This book gives a solid mathematical foundation to, and details the key concepts and algorithms in, this important topic"--
Subject(s)
Genre(s)
ISBN
9780198714934 (hardback)
Bibliography Note
Includes bibliographical references (pages [345]-352) and index.
View MARC record | catkey: 46200113