Computational Research on Cognition and Memory Mechanism in Neural Networks with Asymmetric and Symmetric Network Structures
Project/Area Number |
17500154
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Single-year Grants |
Section | 一般 |
Research Field |
Sensitivity informatics/Soft computing
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Research Institution | Aichi Institute of Technology |
Principal Investigator |
ISHII Naohiro Aichi Institute of Technology, Department of Business and Information Science, Professor, 経営情報科学部, 教授 (50004619)
|
Co-Investigator(Kenkyū-buntansha) |
SUZUKI Susumu Aichi Institute of Technology, Dept. of Business & Inf.Sci., Professor, 経営情報科学部, 教授 (80206490)
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Project Period (FY) |
2005 – 2006
|
Project Status |
Completed (Fiscal Year 2006)
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Budget Amount *help |
¥3,500,000 (Direct Cost: ¥3,500,000)
Fiscal Year 2006: ¥1,100,000 (Direct Cost: ¥1,100,000)
Fiscal Year 2005: ¥2,400,000 (Direct Cost: ¥2,400,000)
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Keywords | asymmetric structure / nonlinear neural network / asymmetric and nonlinear network / Wiener analysis / movement detection / visual cortex V1 and MT / even and odd nonlinearities / optimization of networks / 非線形回路の最適化 / 非対称、非線形神経回路 / 偶数次と奇数次の非線形性 |
Research Abstract |
In the neural networks, a parallel processing with nonlinear characteristics for the spatial information will be a fundamental principle of the visual information processing. It is not well discussed theoretically to clarify the key features for the parallel processing with nonlinear characteristics in the neural networks. In this research, it is shown that the asymmetrical nonlinear functions in the cascaded network with two network layers, play an crucial role in the parallel processing in the movement detection. Then, an ensemble processing of the parallel processing, is newly developed here. We made clear that the parallel processing with the even and odd nonlinear functions, is an effective in the-movement detection. The visual cortex for the movement detection, consists of two layered networks, called the primary visual cortex (V1), followed by the middle temporal area (MT). The fundamental characteristics of the neural network structure in V1 and MT of the visual cortex, is an asymmetrical network with a nonlinear pathway and a linear pathway The model neurons, clarified by Prof Naka at New York York University are discussed by analyzing the asymmetric neural networks. Then the analysis method was applied to the visual cortex networks. The V1 and MT model networks, are decomposed into sub-asymmetrical networks. By the optimization of the asymmetric networks, the movement detection equations are derived. Then, it was clarified that the ensemble parallel processing with the even-odd nonlinearity combined asymmetric networks in the V1 and MT, are fundamental in the movement detection. It was concluded that the ensemble parallel processing of V1 network, followed by the MT network, process the movement information sufficiently from the view point of the computational aspects. The ensemble processing developed here was applied to the text mining problems
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Report
(3 results)
Research Products
(23 results)