Name
Abstract | ||
|---|---|---|
An associative neural network with chaotic neuron model and synaptic depression (CSDNN) is constructed. Memory switching phenomenon in the network is demonstrated. Simulation results show that with various parameter value settings and with various initial conditions, the memory retrieval frequency of CSDNN distributes uniformly among the stored patterns, and the rate of memory retrieval of CSDNN is much higher than that of a chaotic neural network. The possible utilization of memory retrieval in CSDNN is also discussed. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11494669_80 | IWANN |
Keywords | Field | DocType |
chaotic neuron model,various initial condition,synaptic depression,various parameter value setting,associative neural network,simulation result,possible utilization,memory retrieval frequency,chaotic neural network,dynamic synapsis,memory retrieval,initial condition,neural network | Synapse,Associative property,Biological neuron model,Pattern recognition,Bidirectional associative memory,Computer science,Recurrent neural network,Initial value problem,Artificial intelligence,Artificial neural network,Chaotic | Conference |
Volume | ISSN | ISBN |
3512 | 0302-9743 | 3-540-26208-3 |
Citations | PageRank | References |
3 | 0.44 | 6 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhijie Wang | 1 | 89 | 11.14 |
| Hong Fan | 2 | 3 | 0.44 |