Sampling Moments and Reconstructing Signals of Finite Rate of Innovation: Shannon Meets Strang–Fix
نویسندگان
چکیده
منابع مشابه
Sampling signals with finite rate of innovation
Consider classes of signals which have a ̄nite number of degrees of freedom per unit of time, and call this number the rate of innovation of a signal. Examples of signals with ̄nite rate of innovation include stream of Diracs (e.g. the Poisson process), non-uniform splines and piecewise polynomials. Eventhough these signals are not bandlimited, we show that they can be sampled uniformly at (or ab...
متن کاملReconstructing Signals with Finite Rate of Innovation from Noisy Samples
A signal is said to have finite rate of innovation if it has a finite number of degrees of freedom per unit of time. Reconstructing signals with finite rate of innovation from their exact average samples has been studied in SIAM J. Math. Anal., 38(2006), 1389-1422. In this paper, we consider the problem of reconstructing signals with finite rate of innovation from their average samples in the p...
متن کاملCompressive Sampling of EEG Signals with Finite Rate of Innovation
Analyses of electroencephalographic signals and subsequent diagnoses can only be done effectively on long term recordings that preserve the signals’ morphologies. Currently, electroencephalographic signals are obtained at Nyquist rate or higher, thus introducing redundancies. Existing compression methods remove these redundancies, thereby achieving compression. We propose an alternative compres...
متن کاملSampling signals with finite rate of innovation: the noisy case
In [1] a sampling theorem for a certain class of signals with finite rate of innovation (which includes for example stream of Diracs) has been developed. In essence, such non band-limited signals can be sampled at or above the rate of innovation. In the present paper, we consider the case of such signals when noise is present. Clearly, the finite rate of innovation property is lost, but if the ...
متن کاملNonuniform Average Sampling and Reconstruction of Signals with Finite Rate of Innovation
From an average (ideal) sampling/reconstruction process, the question arises whether and how the original signal can be recovered from its average (ideal) samples. We consider the above question under the assumption that the original signal comes from a prototypical space modelling signals with finite rate of innovation, which includes finitely-generated shift-invariant spaces, twisted shift-in...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Signal Processing
سال: 2007
ISSN: 1053-587X
DOI: 10.1109/tsp.2006.890907