Digital Alias-free Signal Processing (PDF)

As demand for applications working in extended frequency ranges
increases, classical Digital signal processing (DSP) techniques,
not protected against aliasing, are becoming less effective.
Digital alias-free signal processing (DASP) is a technique for
overcoming the problems of aliasing at extended frequency ranges.
Based on non-uniform or randomised sampling techniques and the
development of novel algorithms, it creates the capacity to
suppress potential aliasing crucial for high frequency applications
and to reduce the complexity of designs.

This book provides practical and comprehensive coverage of the
theory and techniques behind alias-free digital signal
processing.

Key features:

* Analyses issues of sampling, randomised and pseudo-randomised
quantisation and direct and indirectly randomised sampling.

* Examines periodic and hybrid sampling, including information on
processing algorithms and potential limitations imposed by signal
dynamics.

* Sets out leading methods and techniques for complexity reduced
designs, in particular designs of large aperture sensor arrays,
massive data acquisition and compression from a number of signal
sources and complexity-reduced processing of non-uniform data.

* Presents examples of engineering applications using these
techniques including spectrum analysis, waveform reconstruction and
the estimation of various parameters, emphasising the importance of
the technique for developing new technologies.

* Links DASP and traditional technologies by mapping them into
embedded systems with standard inputs and outputs.

Digital Alias-free Signal Processing is ideal for
practising engineers and researchers working on the development of
digital signal processing applications at extended frequencies. It
is also a valuable reference for electrical and computer
engineering graduates taking courses in signal processing or
digital signal processing.