Fourier analysis and applications: filtering, numerical computation, wavelets
Fourier analysis and applications: filtering, numerical computation, wavelets
Digital Signal Processing: A Computer Based Approach
Digital Signal Processing: A Computer Based Approach
Frequency Domain Analysis of Signals With Stochastic Sampling Times
IEEE Transactions on Signal Processing - Part II
Efficient arbitrary sampling rate conversion with recursivecalculation of coefficients
IEEE Transactions on Signal Processing
Precompensation for anticipated erasures in LTI interpolation systems
IEEE Transactions on Signal Processing
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Decimating a uniformly sampled signal a factor D involves low-pass antialias filtering with normalized cutoff frequency 1/D followed by picking out every Dth sample. Alternatively, decimation can be done in the frequency domain using the fast Fourier transform (FFT) algorithm, after zero-padding the signal and truncating the FFT. We outline three approaches to decimate non-uniformly sampled signals, which are all based on interpolation. The interpolation is done in different domains, and the intersample behavior does not need to be known. The first one interpolates the signal to a uniformly sampling, after which standard decimation can be applied. The second one interpolates a continuous-time convolution integral, that implements the antialias filter, after which every Dth sample can be picked out. The third frequency domain approach computes an approximate Fourier transform, after which truncation and IFFT give the desired result. Simulations indicate that the second approach is particularly useful. A thorough analysis is therefore performed for this case, using the assumption that the non-uniformly distributed sampling instants are generated by a stochastic process.