DocumentCode :
2831109
Title :
On the information transmission ability measurement of neurons via fuzzy method
Author :
Wu, Chia-Chou ; Chen, Bor-Sen
Author_Institution :
Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan
fYear :
2012
fDate :
June 30 2012-July 2 2012
Firstpage :
13
Lastpage :
18
Abstract :
Information processing is an important characteristic of biological neurons. Here, we proposed a method to measure the information transmission ability of neurons. Due to the nonlinear dynamics of neuron, which is experimentally verified, we have to solve the Hamilton-Jacobi inequalities (HJIs) to get the information transmission ability of neuron. Instead of directly solving HJIs, fuzzy interpolation method was employed to help us to systematically measure information transmission ability by solving a set of linear matrix inequalities (LMIs). The information transmission ability measurement method will provide an insight into the mechanism of information processing in neurons.
Keywords :
fuzzy set theory; interpolation; linear matrix inequalities; neurophysiology; Hamilton-Jacobi inequalities; LMI; biological neuron; fuzzy interpolation method; fuzzy method; information processing; linear matrix inequalities; neuron information processing mechanism; neuron information transmission ability measurement; neuron nonlinear dynamics; Biological system modeling; Brain modeling; Mathematical model; Neurons; Noise; Optimization; Symmetric matrices; Hindmarsh-Rose model; Information transmission ability; T-S fuzzy model; fuzzy interpolation; linear matrix inequalities (LMIs);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
System Science and Engineering (ICSSE), 2012 International Conference on
Conference_Location :
Dalian, Liaoning
Print_ISBN :
978-1-4673-0944-8
Electronic_ISBN :
978-1-4673-0943-1
Type :
conf
DOI :
10.1109/ICSSE.2012.6257140
Filename :
6257140
Link To Document :
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