Abstract
We address the problem of filtering and prediction of an individual binary sequence based on its noisy past, as an extension to [1]. The performance criterion investigated is the expected fraction of errors. We propose algorithms and compare their performance to that of the best finite state machine (FSM). We improve on previous results [1] by showing that optimum performance can be achieved by Lempel-Ziv-based estimation algorithms.
| Original language | English |
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| Pages (from-to) | 99 |
| Number of pages | 1 |
| Journal | IEEE International Symposium on Information Theory - Proceedings |
| State | Published - 2000 |
| Externally published | Yes |
| Event | 2000 IEEE International Symposium on Information Theory - Serrento, Italy Duration: 25 Jun 2000 → 30 Jun 2000 |