Li, Yan and Wen, Peng (2005) Bayesian model for brain computation. In: 2005 International Conference on Complex Medical Engineering (CME 2005), 15-18 May 2005, Takamatsu, Japan.
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Abstract
[Abstract]: In this paper we describe the human brain as a Bayesian based internal model and use a decomposition strategy to learn and make prediction. This model combines two processes which together contribute to the state estimate and mimic the causal flow of a process by predicting next state given the current state and nerve signal using Bayesian rules.
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| Item Type: | Conference or Workshop Item (Commonwealth Reporting Category E) (Paper) |
|---|---|
| Refereed: | Yes |
| Item Status: | Live Archive |
| Additional Information: | Permanent restricted access to Published version due to publisher copyright policy. |
| Depositing User: | epEditor USQ |
| Faculty / Department / School: | Historic - Faculty of Engineering and Surveying - Department of Electrical, Electronic and Computer Engineering |
| Date Deposited: | 11 Oct 2007 00:31 |
| Last Modified: | 25 Nov 2013 01:06 |
| Uncontrolled Keywords: | Bayesian rule, brain model, state estimate, prediction |
| Fields of Research : | 08 Information and Computing Sciences > 0806 Information Systems > 080603 Conceptual Modelling 11 Medical and Health Sciences > 1109 Neurosciences > 110903 Central Nervous System 09 Engineering > 0903 Biomedical Engineering > 090399 Biomedical Engineering not elsewhere classified |
| URI: | http://eprints.usq.edu.au/id/eprint/908 |
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