Signal processing theory and machine learning / editors, Paulo S.R. Diniz, Program of Electrical Engineering and the Department of Electronics and Computer Engineering, COPPE/Poli, Universidade Federal do Rio de Janeiro, Brazil, Johan A.K. Suykens, KU Leuven, ESAT-SCD/SISTA, Leuven (Heverlee), Belgium, Rama Chellappa, Department of Electrical and Computer Engineering and Center for Automation Research, University of Maryland, College Park, MD, USA, Sergios Theodoridis, Department of Informatics & Telecommunications, University of Athens, Greece.

Format Electronic
EditionFirst edition.
Publication InfoKidlington, Oxford : Academic Press is an imprint of Elsevier, 2014.
Descriptionli, 1506 pages : illustrations ; 25 cm.
Supplemental ContentFull text available from eBook - Engineering 2014 [EBCE14]
Subjects
Signal processing.

Other author/creatorDiniz, Paulo Sergio Ramirez, 1956-
Other author/creatorSuykens, Johan A. K.
Other author/creatorChellappa, Rama.
Other author/creatorTheodoridis, Sergios, 1951-
SeriesAcademic Press library in signal processing ; volume 1
Academic Press library in signal processing ; volume 1. UNAUTHORIZED
Contents Introduction to Signal Processing Theory / Isabela F. Apolinário and Paulo S.R. Diniz -- Continuous-Time Signals and Systems / José Antonio Apolinário Jr. and Carla L. Pagliari -- Discrete-Time Signals and Systems / Leonardo G. Baltar and Josef A. Nossek -- Random Signals and Stochastic Processes / Luiz Wagner Pereira Biscainho -- Sampling and Quantization / Håkan Johansson -- Digital Filter Structures and their Implementation / Lars Wanhammar and Ya Jun Yu -- Multirate Signal Processing for Software Radio Architectures / Fred Harris, Elettra Venosa and Xiaofei Chen -- Modern Transform Design for Practical Audio/Image/Video Coding Applications / Trac D. Tran -- Discrete Multi-Scale Transforms in Signal Processing / Yufang Bao and Hamid Krim -- Frames in Signal Processing / Lisandro Lovisolo and Eduardo A.B. da Silva -- Parametric Estimation / Suleyman Serdar Kozat and Andrew C. Singer -- Adaptive Filters / Vítor H. Nascimento and Magno T.M. Silva -- Introduction to Machine Learning / Johan A.K. Suykens -- Learning Theory / Ambuj Tewari and Peter L. Bartlett -- Neural Networks / Barbara Hammer -- Kernel Methods and Support Vector Machines / John Shawe-Taylor and Shiliang Sun -- Online Learning in Reproducing Kernel Hilbert Spaces / Konstantinos Slavakis, Pantelis Bouboulis and Sergios Theodoridis -- Introduction to Probabilistic Graphical Models / Franz Pernkopf, Robert Peharz and Sebastian Tschiatschek -- A Tutorial Introduction to Monte Carlo Methods, Markov Chain Monte Carlo and Particle Filtering / A. Taylan Cemgil -- Clustering / Dao Lam and Donald C. Wunsch -- Unsupervised Learning Algorithms and Latent Variable Models: PCA/SVD, CCA/PLS, ICA, NMF, etc / Andrzej Cichocki -- Semi-Supervised Learning / Xueyuan Zhou and Mikhail Belkin -- Sparsity-Aware Learning and Compressed Sensing: An Overview / Sergios Theodoridis, Yannis Kopsinis and Konstantinos Slavakis -- Information Based Learning / José C. Principe, Badong Chen and Luis G. Sanchez Giraldo -- A Tutorial on Model Selection / Enes Makalic, Daniel Francis Schmidt and Abd-Krim Seghouane -- Music Mining / George Tzanetakis.
Bibliography noteIncludes bibliographical references and index.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Genre/formElectronic books.
LCCN 2015430775
ISBN9780123965028
ISBN0123965020

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