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Introduction to statistical signal processing with applications Mandyam D. Srinath, P.K. Rajasekaran, R. Viswanathan
Publisher: Prentice Hall

Shastri Anant R., Element of Differential Topology, CRC, February 2011. Introduction and Overview; Fourier Transforms and Theorems. Brad Efron and Carl Morris's 1977 Scientific American paper is an awesome intro on Stein Paradox for anyone who is uninitiated in statistics like me. Short-Vector SIMD Parallelization in Signal Processing Rade Kutil. This is all the more surprising given that shrinkage estimators are used routinely. Spectral Audio Signal Processing online book. Appropriate for introductory graduate-level courses in Statistical Signal Processing and Detection and Estimation Theory. The most complete overview of signal detection available. Statistical Methods, 3rd Edition; Academic Press, January 2011. FFT Implementation of the Phase Vocoder; Phase Vocoder Applications. The series has been written to provide the reader with a broad introduction to the theory and application of statistical signal processing. Parallel SVD Computing in the Latent Semantic Indexing Applications for Data Retrieval Gabriel Okša and Marián Vajteršic. Probability, Random Variables, and Random Processes: Theory and Signal Processing Applications (0470242094 Sufficient statistics are covered in detail, as is their connection to parameter estimation techniques. Posted May 19, 2013 at 10:03 am | Permalink. Fundamentals of Statistical Signal Processing, Volume II: Detection Theory by Steven M. At a minimum, we require each of our majors to complete an Introduction to Electrical and Computer Engineering course containing an embedded systems module, a basic course in digital design, and a first course in microprocessor programming . Http://www-stat.stanford.edu/~ckirby/brad/other/Article1977.pdf. Lamentably in (statistical) signal processing applications, we do not teach this at all.