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The Application of Celluar Neural Network and the Algorithm Hardware Implematation

Author: LuShanPing
Tutor: YuShengLin
School: Nanjing University of Aeronautics and Astronautics
Course: Measuring Technology and Instruments
Keywords: Cellular neural networks Edge Detection Particle swarm optimization Moving Object Segmentation Morphological reconstruction FPGA
CLC: TP183
Type: Master's thesis
Year: 2009
Downloads: 38
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Abstract


CNN is a neural network based on local interconnects , ultra-large-scale integration (VLSI) technology to achieve an easy parallel microprocessor unit , particularly suitable for applications in the field of visual image processing and recognition , in recent years, artificial neural network a hot research field . This paper studies the template design of cellular neural network (CNN) , the hardware design of the the CNN algorithm in image processing applications as well as CNN algorithm . CNN 's template design for image edge detection , and computer simulation designed templates . Same time cellular neural network constructed with FPGA real-time image processing . In this paper, both theoretical and practical aspects of research and discusses the key algorithms and techniques involved in the process of system implementation . The papers include the following : ( 1) research and application of cellular neural networks . Principle and structure of cellular neural networks . CNN dynamic mechanisms , analysis of the stability of CNN . (2) design the templates of cellular neural networks . By particle swarm algorithm design templates of cellular neural networks applied to image edge detection , and achieved good results. And compared with the genetic algorithm , particle swarm algorithm has better convergence and accuracy . (3 ) for a relatively static background of video sequences , the design of a cellular neural network - based video motion object segmentation algorithm to complete the program Matlab7.0 experimental software platform - based design , through the analysis of experimental results further improved algorithm , that is in the video pretreatment process , the use the CNN algorithms constitute the morphological reconstruction of image filtering , the experimental results show that the segmentation algorithm has better performance and application advantages . (4 ) discuss the CNN algorithm - based hardware FPGA design ideas, using Verilog HDL language to describe the CNN algorithm , the template edge detection value as the value of the input signal of the hardware template , by the Quartus II environment for algorithm verification CNN edge detection algorithm hardware implementation and simulation results , the results show that the hardware implementation is feasible .

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CLC: > Industrial Technology > Automation technology,computer technology > Automated basic theory > Artificial intelligence theory > Artificial Neural Networks and Computing
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