@是一本介Bnon-uniform sampling理的, 跟一般大家熟悉的作法不太一
Digital Alias-free Signal Processing (DASP) is a set of methodologies that use
nonuniform sampling and specialised signal processing algorithms that allow
processing signals with unknown spectral support in the frequency ranges that are
wider than half the average sampling rate.
热萁榻B:
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.
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
我要上传