Posted by **BUGSY** at April 30, 2015

English | Oct 31, 2006 | ISBN: 1905209452 | 386 Pages | PDF | 4 MB

Dealing with digital filtering methods for 1-D and 2-D signals, this book provides the theoretical background in signal processing, covering topics such as the z-transform, Shannon sampling theorem and fast Fourier transform. An entire chapter is devoted to the design of time-continuous filters which provides a useful preliminary step for analog-to-digital filter conversion.

Posted by **ChrisRedfield** at April 26, 2017

Published: 2011-12-21 | ISBN: 1439855137, 1138072168 | PDF | 858 pages | 185.33 MB

Posted by **interes** at Feb. 21, 2017

English | 2017 | ISBN: 1498776450 | 444 pages | PDF | 15 MB

Posted by **step778** at Feb. 20, 2017

2006 | pages: 177 | ISBN: 3540370110 | PDF | 5,4 mb

Posted by **step778** at May 20, 2016

2011 | pages: 608 | ISBN: 047074183X | PDF | 7,2 mb

Posted by **tanas.olesya** at Dec. 22, 2015

English | 6 May 2004 | ISBN: 052183127X | 232 Pages | PDF | 1 MB

The statistical bootstrap is one of the methods that can be used to calculate estimates of a certain number of unknown parameters of a random process or a signal observed in noise, based on a random sample.

Posted by **arundhati** at July 19, 2015

2012 | ISBN-10: 1439855137 | 857 pages | PDF | 185 MB

Posted by **arundhati** at Jan. 17, 2015

2010 | ISBN: 0521190495, 0511776373 | 466 pages | PDF | 3 MB

Posted by **tanas.olesya** at Dec. 13, 2014

English | August 14, 1999 | ISBN: 0201361868 | 978 pages | PDF | 38 MB

Mathematical Methods and Algorithms for Signal Processing tackles the challenge of providing readers and practitioners with the broad tools of mathematics employed in modern signal processing. Building from an assumed background in signals and stochastic processes, the book provides a solid foundation in analysis, linear algebra, optimization, and statistical signal processing.

Posted by **tanas.olesya** at Dec. 4, 2014

English | September 29, 1998 | ISBN: 0849385792 | 820 pages | PDF | 10 MB

Signal processing is a broad and timeless area. The term "signal" includes audio, video, speech, image, communication, geophysical, sonar, radar, medical, and more. Signal processing applies to the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals.