Recovery of the optimal approximation from samples in wavelet subspace
Digital Signal Processing
| Hi-index | 35.68 |
The error estimate is useful in the application of the sampling theorem. For the classical Shannon sampling theorem, various errors are widely studied, but for the sampling theorem in general wavelet subspaces, only the aliasing error is studied. In this paper, we study three other errors: truncation error, amplitude error, and time-jitter error. With the same technique, a result on irregular sampling is improved