Title :
Hierarchical encoding of human working memory
Author :
Guoqi Li;Jing Pei;Changyun Wen;Zhengguo Li;Guangshe Zhao;Luping Shi
Author_Institution :
Center for Brain Inspired Research (CBICR), Department of Precision Instrument, Tsinghua University, Beijing, China, 100084
fDate :
6/1/2015 12:00:00 AM
Abstract :
A model for encoding and the retrieve of the sequential working memory is proposed by using bidirectional inhibition-connected neural networks with winnerless competition. It is found that the retrieve accuracy is dependent on the encoding time the the properties of the neural inhibition weights. The simulation results shows the effectiveness of our proposed model.
Keywords :
"Neurons","Mathematical model","Predator prey systems","Encoding","Psychology","Analytical models","Biological neural networks"
Conference_Titel :
Industrial Electronics and Applications (ICIEA), 2015 IEEE 10th Conference on
DOI :
10.1109/ICIEA.2015.7334232
