Abstract
We discuss the trade-off between sampling and quantization in signal processing for the purpose of minimizing the error of the reconstructed signal subject to the constraint that the digitized signal fits in a given amount of memory. For signals with different regularities, we estimate the intrinsic errors from finite sampling and quantization, and determine the sampling and quantization resolutions.
| Original language | English |
|---|---|
| Pages (from-to) | 359-371 |
| Number of pages | 13 |
| Journal | Journal of Complexity |
| Volume | 3 |
| Issue number | 4 |
| DOIs | |
| State | Published - Dec 1987 |
Bibliographical note
Funding Information:* Research supported by the NSF under Grant IRI-8702168. Parts were done while the author was a consultant with the AT&T Bell Laboratories. t Research supported by the NSF under Grant DCR-86-03674. Current address: Department of Computer Science, University of Kentucky, Lexington, KY 40506.
Funding
* Research supported by the NSF under Grant IRI-8702168. Parts were done while the author was a consultant with the AT&T Bell Laboratories. t Research supported by the NSF under Grant DCR-86-03674. Current address: Department of Computer Science, University of Kentucky, Lexington, KY 40506.
| Funders | Funder number |
|---|---|
| National Science Foundation Arctic Social Science Program | 8702168, DCR-86-03674, IRI-8702168 |
ASJC Scopus subject areas
- Algebra and Number Theory
- Statistics and Probability
- Numerical Analysis
- General Mathematics
- Control and Optimization
- Applied Mathematics
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