منابع مشابه
Signal Extrapolation in Wavelet Subspaces
Abstract. The Papoulis-Gerchberg (PG) algorithm is well known for band-limited signal extrapolation. The authors consider the generalization of the PG algorithm to signals in the wavelet subspaces in this research. The uniqueness of the extrapolation for continuous-time signals is examined, and sufficient conditions on signals and wavelet bases for the generalized PG (GPG) algorithm to converge...
متن کاملOn the convergence of wavelet-based iterative signal extrapolation algorithms
A generalized Papoulis-Gerchberg (PG) algorithm for signal extrapolation based on the wavelet representation has been recently proposed by Xia, Kuo and Zhang. In this research, we examine the convergence property and the convergence rate of several signal extrapolation algorithms in wavelet subspaces. We first show that the generalized PG algorithm converges to the minimum norm solution when th...
متن کاملOversampling in Wavelet Subspaces
Recently, several extensions of classical Shannon sampling theory to wavelet subspaces have been reported. This paper is devoted to uniform and periodic nonuniform oversampling in wavelet subspaces. Specifically, we provide a stability analysis and we introduce a technique for calculating the condition number of wavelet subspace sampling operators. It is shown that oversampling results in impro...
متن کاملAnalysis and short-time extrapolation of stock market indexes through projection onto discrete wavelet subspaces
We consider the problem of short-time extrapolation of blue chips’ stocks indexes in the context of wavelet subspaces following the theory proposed by X.-G. Xia and co-workers in a series of papers [29,28,14,15]. The idea is first to approximate the oscillations of the corresponding stock index at some scale by means of the scaling function which is part of a given multi-resolution analysis of ...
متن کاملOversampling Expansion in Wavelet Subspaces
We find necessary and sufficient conditions for (shifted) oversampling expansions to hold in wavelet subspaces. In particular, we characterize scaling functions with the (shifted) oversampling property. We also obtain L and L∞ norm estimates for the truncation and aliasing errors of the oversampling expansion.
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ژورنال
عنوان ژورنال: SIAM Journal on Scientific Computing
سال: 1995
ISSN: 1064-8275,1095-7197
DOI: 10.1137/0916005