2篇
您的检索式：作者名="SHIMeihong"
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| 1 | Filtering images contaminated with pep and salt type noise with pulse-coupled neural networks显示文摘Pulse coupled neural network (PCNN) has a specific feature that the fire of one neuron can capture its adjacent neurons to fire due to their spatial proximity and intensity similarity. In this paper, it is indicated that this feature itself is a very good mechanism for image filtering when the image is damaged with pep and salt (PAS) type noise. An adaptive filtering method, in which the noisy pixels are first located and then filtered based on the output of the PCNN, is presented. The threshold function of a neuron in the PCNN is designed when it is used for filtering random PAS and extreme PAS noise contaminated image respectively. The filtered image has no distortion for noisy pixels and only less mistiness for non-noisy pixels, compared with the conventional window-based filtering method. Excellent experimental results show great effectiveness and efficiency of the proposed method, especially for heavy-noise contaminated images. | ZHANGJunying LUZhijun SHILin DONGJiyang SHIMeihong | 2005 | Science in China(Series F)2005，48，3： | 12 |
| 2 | Output-threshold coupled neural network for solving the shortest path problems显示文摘This paper presents a coupled neural network, called output-threshold coupled neural network (OTCNN), which can mImic the autowaves in the present pulsed coupled neural networks (PCNNs), by the construction of mutual coupling between neuron outputs and the threshold of a neuron. Based on its autowaves, this paper presents a method for finding the shortest path in shortest time with OTCNNs. The method presented here features much fewer neurons needed, simplicity of the structure of the neurons and the networks, and large scale of parallel computation. It is shown that OTCNN is very effective in finding the shortest paths from a single start node to multiple destination nodes for asymmetric weighted graph, with a number of iterations proportional only to the length of the shortest paths, but independent of the complexity of the graph and the total number of existing paths in the graph. Finally, examples for finding the shortest path are presented. | ZHANGJunying WANGDefeng SHIMeihong WANGJosephYue | 2004 | Science in China(Series F)2004，47，1： | 3 |
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