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Research on Biological Lateral Inhibitory Mechanism and Its Application

Author: DuHongWei
Tutor: WangCongQing
School: Nanjing University of Aeronautics and Astronautics
Course: Pattern Recognition and Intelligent Systems
Keywords: Lateral inhibition network Calculus lateral inhibition model Target detection Lateral inhibition of cortical columns Neural network group Location tracking
CLC: TP391.41
Type: Master's thesis
Year: 2008
Downloads: 138
Quote: 2
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Abstract


Lateral inhibition is one of the basic principles of information processing in the nervous system. From the horseshoe crab is so original the arthropods to people from all levels of the peripheral nervous system until the central side, from tactile to visual sensory system inhibition. Lateral inhibition has broad application prospects in the field of image processing, pattern recognition, artificial intelligence, imaging guidance. Cutting-edge neuroscience theory to explore this article contralateral suppression mechanism, and focuses on the application of contralateral suppression mechanism to conduct an in-depth study. First, in the area of ??image processing, digital acyclic common side inhibitory networks bimodal Gaussian distribution acyclic lateral inhibition network applied to image enhancement, image processing \improved edge detection algorithm based shunt suppression mechanism, edge extraction is better than the conventional algorithms; addition, the lateral inhibition mechanism of pulse coupled neural network combined with a pulse coupled neural network based on lateral inhibition image segmentation, image segmentation has good connectivity. Subsequently, a new moving target detection method based on temporal and spatial information. The introduction of the method of the calculus side suppression (Algorithmic Lateral Inhibition referred ALI) model and multi-channel of the concept and the video images, respectively, on each channel carry out time-domain ALI when airspace ALI operator to obtain motion information, and use of airspace ALI eliminate noise. Simulation results show that the method can accurately obtain the complex background of the outline of the moving target. Followed by the establishment of a based on the The cortical columns lateral inhibition mechanism of neural network group, analog cerebral cortex column impulses phenomenon, and the neural network group location tracking. The successively Stein neurons and improved Hodgkin-Huxley neurons Construction neural network base, lateral inhibition of cortical columns and cortical columns respectively applied to the neural network group encoding, decoding, and negatively correlated neural network base ignition. Application of lateral inhibition mechanisms of cortical columns greatly improved location tracking accuracy and system stability. Finally, the theoretical analysis focusing on the cycle lateral inhibition network WTA competition features to achieve a \WTA neural network group.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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