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10 years of news and resources for members of the IEEE Signal Processing Society

New Books

Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep.

This book is a comprehensive guide to the theory and practice of signal enhancement and array signal processing, including Matlab codes, exercises, and instructor and solution manuals. Written as a course textbook for senior undergraduate and graduate students, it contains a total of 11 chapters, which cover single-channel signal enhancement and multichannel signal enhancement in the time and frequency domains.

We would like to highlight the second edition of "Time-Frequency Signal Analysis and Processing: A Comprehensive Reference" (https://www.elsevier.com/books/time-frequency-signal-analysis-and-processing/boashash/978-0-12-398499-9) by Professor Boualem Boashash. 

Following the successful PCS Auction conducted by the US Federal Communications Commission in 1994, auctions have replaced traditional ways of allocating valuable radio spectrum, a key resource for any mobile telecommunications operator. Spectrum auctions have raised billions of dollars worldwide and have become a role model for market-based approaches in the public and private sectors. The design of spectrum auctions is a central application of game theory and auction theory due to its importance in industry and the theoretical challenges it presents.

"Digital Signal Processing with Kernel Methods" is a new book written by Jose Luis Rojo-Avarez, Manel Martinez-Ramon, Jordi Munoz-Mari, and Gustau Camps-Valls.

A.N. Akansu, S.R. Kulkarni and D.M. Malioutov, Eds., Financial Signal Processing and Machine Learning

ISBN: 978-1-118-74567-0

URL: http://www.wiley.com/WileyCDA/WileyTitle/productCd-1118745671.html

Description

Financial Signal Processing and Machine Learning, A.N. Akansu, S.R. Kulkarni and D.M. Malioutov, Eds. Wiley-IEEE Press, 2016.

"Discrete Fourier and Wavelet Transforms: An Introduction through Linear Algebra with Applications to Signal Processing" is a new undergraduate textbook authored by Roe W Goodman from Rutgers University. This textbook for undergraduate mathematics, science, and engineering students introduces the theory and applications of discrete Fourier and wavelet transforms using elementary linear algebra, without assuming prior knowledge of signal processing or advanced analysis.

A.N. Akansu and M.U. Torun, A Primer for Financial Engineering, Financial Signal Processing and Electronic Trading. Elsevier, 2015.

http://store.elsevier.com/A-Primer-for-Financial-Engineering/Ali-Akansu/...

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