Liu, Wenbin, Chen, Neiping, Feng, Jianfeng (2006) Sufficient and necessary condition for the convergence of stochastic approximation algorithms. Probability and Statistics Letter, 76 (2). pp. 203-210. ISSN 0167-7152. (doi:10.1016/j.spl.2005.07.020) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:8487)
| The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
| Official URL: https://doi.org/10.1016/j.spl.2005.07.020 |
Abstract
We present a sufficient and necessary condition for the convergence of stochastic approximation algorithms, which were proposed 50 years ago, have been widely applied to various areas and intensively investigated in theory. In the literature, only various sufficient conditions are known. The obtained condition is simple and has a clear physical meaning.
| Item Type: | Article |
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| DOI/Identification number: | 10.1016/j.spl.2005.07.020 |
| Uncontrolled keywords: | stochastic approximation algorithms; simulated annealing; local minima; global minima |
| Subjects: | H Social Sciences > HA Statistics > HA33 Management Science |
| Divisions: | Divisions > Kent Business School - Division > Kent Business School (do not use) |
| Depositing User: | Steve Liu |
| Date Deposited: | 07 Sep 2008 15:21 UTC |
| Last Modified: | 05 Nov 2024 09:40 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/8487 (The current URI for this page, for reference purposes) |
University of Kent Author Information
Liu, Wenbin.
| Creator's ORCID: |
 https://orcid.org/0000-0001-5966-6235
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