학술논문

Neurocomputation of image motion
Document Type
Conference
Author
Source
1990 IJCNN International Joint Conference on Neural Networks Neural Networks, 1990., 1990 IJCNN International Joint Conference on. :401-406 vol.1 1990
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Components, Circuits, Devices and Systems
Signal Processing and Analysis
Language
Abstract
The Shannon information theory is used to analyze a simple three-layer feedforward neural net. The central assumption is that the transmission channel from the top layer of the network to the middle layer has a short-term memory of the past history of the incoming visual signal. The criterion for the emergence of motion detection is to demand that the output signals from the bottom layer sent signals belonging to statistically independent events in the output signal space. It is shown that the network operates with different modes. One active mode is identified to have the ability to detect the temporal changes of the visual signals and the direction of the image motion. These are shown analytically

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