Abstract
A stochastic algorithm, familiar from adaptive estimation, is introduced and its homogeneous part is shown to be exponentially convergent for a wide class of inputs, which need not be stationary. The implications of this convergence rate for the non-homogeneous algorithm in practical situations are qualitatively examined and a possible approach to improving performance in use is suggested.
| Original language | English |
|---|---|
| Pages (from-to) | 580-585 |
| Number of pages | 6 |
| Journal | Proceedings of the IEEE Conference on Decision and Control |
| DOIs | |
| Publication status | Published - 1978 |
| Event | Proc IEEE Conf Decis Control Incl Symp Adapt Processes 17th - San Diego, CA, USA Duration: 10 Jan 1979 → 12 Jan 1979 |
Fingerprint
Dive into the research topics of 'EXPONENTIALLY CONVERGENT BEHAVIOUR OF SIMPLE STOCHASTIC ADAPTIVE ESTIMATION ALGORITHMS.'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver