Academic Press Library in Signal Processing

Academic Press Library in Signal Processing, 1st Edition

Signal Processing Theory and Machine Learning

Academic Press Library in Signal Processing, 1st Edition,Sergios Theodoridis,Rama Chellappa,ISBN9780123965028

Theodoridis  &   Chellappa   

Academic Press




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Quickly grasp and understand the key principles in Theory, Speech and Acoustic Processing, and Machine Learning from world leading experts

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Key Features

  • 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


This first volume, 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


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Sergios Theodoridis

Sergios Theodoridis acquired a Physics degree with honors from the University of Athens, Greece in 1973 and a MSc and a Ph.D. degree in Signal Processing and Communications from the University of Birmingham, UK in 1975 and 1978 respectively. Since 1995 he has been a Professor with the Department of Informatics and Communications at the University of Athens.

Affiliations and Expertise

Department of Informatics and Telecommunications, University of Athens, Greece

View additional works by Sergios Theodoridis

Rama Chellappa

Affiliations and Expertise

University of Maryland, College Park, MD, USA

View additional works by Rama Chellappa

Academic Press Library in Signal Processing, 1st Edition

CHAPTER 1 Introduction to Signal Processing Theory- Isabela Ferrão Apolinário and Paulo S.R. Diniz

CHAPTER 2 Continuous-Time Signals and Systems- José Antonio Apolinário Jr. and Carla L. Pagliari

CHAPTER 3 Discrete-Time Signals and Systems- Leonardo Gomes Baltar and Josef A. Nossek

CHAPTER 4 Random Signals and Stochastic Processes- Luiz Wagner Pereira Biscainho

CHAPTER 5 Sampling and Quantization- Håkan Johansson

CHAPTER 6 Digital Filter Structures and their Implementation- Lars Wanhammar and Ya Jun Yu

CHAPTER 7 Multirate Signal Processing for Software Radio Architectures- Fred Harris, Elettra Venosa and Xiaofei Chen

CHAPTER 8 Modern Transform Design for Practical Audio/Image/Video Coding Applications- Trac D. Tran

CHAPTER 9 Discrete Multi-Scale Transforms in Signal Processing- Yufang Bao and Hamid Krim

CHAPTER 10 Frames in Signal Processing- Lisandro Lovisolo and Eduardo A. B. da Silva

CHAPTER 11 Parametric Estimation- Suleyman Serdar Kozat and Andrew C. Singer

CHAPTER 12 Adaptive Filters- Vítor H. Nascimento and Magno T. M. Silva

CHAPTER 13 Introduction to Machine Learning- Johan A.K. Suykens

CHAPTER 14 Learning Theory- Ambuj Tewari and Peter L. Bartlett

CHAPTER 15 Neural Networks- Barbara Hammer

CHAPTER 16 Kernel Methods and Support Vector Machines- John Shawe-Taylor and Shiliang Sun

CHAPTER 17 Online Learning in Reproducing Kernel Hilbert Spaces- Konstantinos Slavakis, Pantelis Bouboulis and Sergios Theodoridis

CHAPTER 18 Introduction to Probabilistic Graphical Models- Franz Pernkopf, Robert Peharz and Sebastian Tschiatschek

CHAPTER 19 A Tutorial Introduction to Monte Carlo Methods, Markov Chain Monte Carlo and Particle Filtering- A. Taylan Cemgil

CHAPTER 20 Clustering- Dao Lam and Donald C.Wunsch

CHAPTER 21 Unsupervised Learning Algorithms and Latent Variable Models: PCA/SVD, CCA/PLS, ICA, NMF, etc- Andrzej Cichocki

CHAPTER 22 Semi-Supervised Learning- Xueyuan Zhou and Mikhail Belkin

CHAPTER 23 Sparsity-Aware Learning and Compressed Sensing: An Overview- Sergios Theodoridis, Yannis Kopsinis and Konstantinos Slavakis

CHAPTER 24 Information Based Learning- José C. Principe, Badong Chen and Luis Gonzalo Sánchez Giraldo

CHAPTER 25 A Tutorial on Model Selection- Enes Makalic, Daniel Francis Schmidt and Abd-Krim Seghouane

CHAPTER 26 Music Mining- George Tzanetakis

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