Signal Processing Theory and Machine Learning

✍ Scribed by Paulo S.R. Diniz, Johan A.K. Suykens, Rama Chellappa and Sergios Theodoridis (Eds.)

• Publisher: Academic Press
• Year: 2014
• Tongue: English
• Leaves: 1518
• Series: Academic Press Library in Signal Processing 1
• Edition: 1
• Category: Library

✦ Synopsis

This first volume of a five volume set, edited and authored by world leading experts, gives a review of the principles, methods and techniques of important and emerging research topics and technologies in machine learning and advanced signal processing theory.

With this reference source you will:

• Quickly grasp a new area of research 
• Understand the underlying principles of a topic and its application
• Ascertain how a topic relates to other areas and learn of the research issues yet to be resolved

• Quick tutorial reviews of important and emerging topics of research in machine learning
• Presents core principles in signal processing theory and shows their applications
• Reference content on core principles, technologies, algorithms and applications
• Comprehensive references to journal articles and other literature on which to build further, more specific and detailed knowledge
• Edited by leading people in the field who, through their reputation, have been able to commission experts to write on a particular topic

✦ Table of Contents

Content:
Copyright
Page iv

Introduction
Pages xxvii-xxix

About the Editors
Pages xxxi-xxxii

Section Editors
Pages xxxiii-xxxiv

Authors Biography
Pages xxxv-li

Chapter 1 - Introduction to Signal Processing Theory Original Research Article
Pages 3-28
Isabela F. Apolinário, Paulo S.R. Diniz

Chapter 2 - Continuous-Time Signals and Systems Original Research Article
Pages 29-78
José A. Apolinário Jr., Carla L. Pagliari

Chapter 3 - Discrete-Time Signals and Systems Original Research Article
Pages 79-112
Leonardo G. Baltar, Josef A. Nossek

Chapter 4 - Random Signals and Stochastic Processes Original Research Article
Pages 113-168
Luiz Wagner Pereira Biscainho

Chapter 5 - Sampling and Quantization Original Research Article
Pages 169-244
Håkan Johansson

Chapter 6 - Digital Filter Structures and Their Implementation Original Research Article
Pages 245-338
Lars Wanhammar, Ya Jun Yu

Chapter 7 - Multirate Signal Processing for Software Radio Architectures Original Research Article
Pages 339-422
Fred Harris, Elettra Venosa, Xiaofei Chen

Chapter 8 - Modern Transform Design for Practical Audio/Image/Video Coding Applications Original Research Article
Pages 423-465
Trac D. Tran

Chapter 9 - Discrete Multi-Scale Transforms in Signal Processing Original Research Article
Pages 467-560
Yufang Bao, Hamid Krim

Chapter 10 - Frames in Signal Processing Original Research Article
Pages 561-590
Lisandro Lovisolo, Eduardo A.B. da Silva

Chapter 11 - Parametric Estimation Original Research Article
Pages 591-618
Suleyman Serdar Kozat, Andrew C. Singer

Chapter 12 - Adaptive Filters Original Research Article
Pages 619-761
Vítor H. Nascimento, Magno T.M. Silva

Chapter 13 - Introduction to Machine Learning Original Research Article
Pages 765-773
Johan A.K. Suykens

Chapter 14 - Learning Theory Original Research Article
Pages 775-816
Ambuj Tewari, Peter L. Bartlett

Chapter 15 - Neural Networks Original Research Article
Pages 817-855
Barbara Hammer

Chapter 16 - Kernel Methods and Support Vector Machines Original Research Article
Pages 857-881
John Shawe-Taylor, Shiliang Sun

Chapter 17 - Online Learning in Reproducing Kernel Hilbert Spaces Original Research Article
Pages 883-987
Konstantinos Slavakis, Pantelis Bouboulis, Sergios Theodoridis

Chapter 18 - Introduction to Probabilistic Graphical Models Original Research Article
Pages 989-1064
Franz Pernkopf, Robert Peharz, Sebastian Tschiatschek

Chapter 19 - A Tutorial Introduction to Monte Carlo Methods, Markov Chain Monte Carlo and Particle Filtering Original Research Article
Pages 1065-1114
A. Taylan Cemgil

Chapter 20 - Clustering Original Research Article
Pages 1115-1149
Dao Lam, Donald C. Wunsch

Chapter 21 - Unsupervised Learning Algorithms and Latent Variable Models: PCA/SVD, CCA/PLS, ICA, NMF, etc. Original Research Article
Pages 1151-1238
Andrzej Cichocki

Chapter 22 - Semi-Supervised Learning Original Research Article
Pages 1239-1269
Xueyuan Zhou, Mikhail Belkin

Chapter 23 - Sparsity-Aware Learning and Compressed Sensing: An Overview Original Research Article
Pages 1271-1377
Sergios Theodoridis, Yannis Kopsinis, Konstantinos Slavakis

Chapter 24 - Information Based Learning Original Research Article
Pages 1379-1414
José C. Príncipe, Badong Chen, Luis G. Sanchez Giraldo

Chapter 25 - A Tutorial on Model Selection Original Research Article
Pages 1415-1452
Enes Makalic, Daniel Francis Schmidt, Abd-Krim Seghouane

Chapter 26 - Music Mining Original Research Article
Pages 1453-1492
George Tzanetakis

Index
Pages 1493-1506