Approximation of wide-sense stationary stochastic processes by Shannon sampling series
IEEE Transactions on Information Theory
Advances in Computational Mathematics
Recovery of the optimal approximation from samples in wavelet subspace
Digital Signal Processing
| Hi-index | 754.90 |
From the Paley-Wiener 1/4-theorem, the finite energy signal f(t) can be reconstructed from its irregularly sampled values f(k+δκ) if f(t) is band-limited and supκ|δκ|<1/4. We consider the signals in wavelet subspaces and wish to recover the signals from its irregular samples by using scaling functions. Then the method of estimating the upper bound of supκ|δκ | such that the irregularly sampled signals can be recovered is very important. Following the work done by Liu and Walter (see J. Fourier Anal. Appl., vol.2, no.2, p.181-9, 1995), we present an algorithm which can estimate a proper upper bound of supκ |δκ|. Compared to Paley-Wiener 1/4-theorem, this theorem can relax the upper bound for sampling in some wavelet subspaces