Introduction to Signal Processing
by Sophocles J. Orfanidis
Publisher: Prentice Hall 2009
Number of pages: 398
Provides an applications-oriented introduction to digital signal processing. Orfandis covers all the basic DSP concepts and methods, such as sampling, discrete-time systems, DFT/FFT algorithms, and filter design. The book emphasizes the algorithmic, computational, and programming aspects of DSP, and includes a large number of worked examples, applications, and computer examples.
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by Jeff Fessler - University of Michigan
Course objectives: 1. to teach students the concepts of discrete-time signals, including mathematical representations; 2. to teach students the concepts of linear time-invariant discrete-time systems; 3. to introduce the concepts of filter design.
by Raghu Raj Bahadur, at al. - IMS
In this volume the author covered what should be standard topics in a course of parametric estimation: Bayes estimates, unbiased estimation, Fisher information, Cramer-Rao bounds, and the theory of maximum likelihood estimation.
by R. M. Gray, L. D. Davisson - Cambridge University Press
The book covers basic probability, random objects, expectation, second order moment theory with examples of the random process models and their basic properties, specific applications for communication, estimation, detection, modulation.
by Paolo Prandoni, Martin Vetterli - EFPL Press
The book is less focused on the mathematics and more on the concepts, allowing students to think about the subject at a higher conceptual level, thus building the foundations for more advanced topics and helping students solve real-world problems.