Name
Abstract | ||
|---|---|---|
To make clear the mechanism of the visual movement is important in the visual system. The problem is how to perceive vectors of the optic flow in the network. First, the biological asymmetric network with nonlinear ties is analyzed for generating the vector from the point of the network computations. The results are applicable to the V1 and MT model of the neural networks in the cortex. The stimulus with a mixture distribution is applied to evaluate their network processing ability for the movement direction and its velocity, which generate the vector. Second, it is shown that the vector is emphasized in the MT than the V1. The characterized equation is derived in the network computations, which evaluates the vector properties of processing ability of the network. The movement velocity is derived, which is represented in Wiener kernels. The operations of vectors are shown in the divisive normalization network, which will create curl or divergence vectors in the higher neural network as MST area. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/SNPD.2013.94 | Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing |
Keywords | Field | DocType |
network processing ability,movement velocity,higher neural network,neural network,network computation,movement direction,vector property,vector operations,neural networks computations,biological asymmetric network,divisive normalization network,divergence vector,vectors,computer architecture,mixture distribution,neural nets,visual system,computer vision,mathematical model,stochastic processes,visual perception,kernel,optic flow,cortex | Tensor product network,Computer science,Random neural network,Stochastic neural network,Probabilistic neural network,Time delay neural network,Artificial intelligence,Artificial neural network,Curl (mathematics),Neural gas,Machine learning | Conference |
Volume | Issue | ISSN |
1 | 2 | 2166-7160 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Naohiro Ishii | 1 | 461 | 128.62 |
| Toshinori Deguchi | 2 | 30 | 12.88 |
| Masashi Kawaguchi | 3 | 24 | 14.93 |
| Hiroshi Sasaki | 4 | 0 | 0.68 |