DocumentCode
2018051
Title
Optimize the distribution of preferred stimulus in a population code
Author
Wu, Si ; Nakahara, Hiroyuki
Author_Institution
Brain Sci. Inst., RIKEN, Saitama, Japan
Volume
1
fYear
1999
fDate
1999
Firstpage
326
Abstract
We consider two methods to optimize the distribution of preferred stimulus in a population code based on the knowledge of the distribution of stimulus. One method is to maximize the mean Fisher information of the population with respect to the stimulus ensemble. The other is to minimize the lower bound of the mean decoding error. The implication of the two methods is discussed
Keywords
neural nets; optimisation; mean Fisher information maximisation; mean decoding error lower bound minimisation; population code; preferred stimulus distribution optimisation; stimulus ensemble; Biological information theory; Chemicals; Cost function; Encoding; Gaussian noise; Maximum likelihood decoding; Maximum likelihood estimation; Mutual information; Neurons; Optimization methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Information Processing, 1999. Proceedings. ICONIP '99. 6th International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-5871-6
Type
conf
DOI
10.1109/ICONIP.1999.844008
Filename
844008
Link To Document