Please use this identifier to cite or link to this item:
http://lib.hpu.edu.vn/handle/123456789/21363
Title: | Advances in Intelligent Signal Processing and Data Mining: Theory and Applications |
Authors: | Mihaylova, Lyudmila Georgieva, Petia Georgieva, Petia Mihaylova, Lyudmila Jain, Lakhmi C. |
Keywords: | Signal processing Data mining Applications |
Issue Date: | 2013 |
Publisher: | Springer-Verlag Berlin Heidelberg |
Series/Report no.: | Studies in Computational Intelligence 410 |
Abstract: | The book presents some of the most efficient statistical and deterministic methods for information processing and applications in order to extract targeted information and find hidden patterns. The techniques presented range from Bayesian approaches and their variations such as sequential Monte Carlo methods, Markov Chain Monte Carlo filters, Rao Blackwellization, to the biologically inspired paradigm of Neural Networks and decomposition techniques such as Empirical Mode Decomposition, Independent Component Analysis and Singular Spectrum Analysis. The book is directed to the research students, professors, researchers and practitioners interested in exploring the advanced techniques in intelligent signal processing and data mining paradigms. |
URI: | https://lib.hpu.edu.vn/handle/123456789/21363 |
ISBN: | 978-3-642-28695-7 978-3-642-28696-4 |
Appears in Collections: | Technology |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
52_Advances_in_Intelligent_Signal_Processing_and_Data.pdf Restricted Access | 19.13 MB | Adobe PDF | ![]() View/Open Request a copy |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.