To simulate the firing pattern of biological grid cells, this paper presents an improved computational model of grid cells based on column structure. In this model, the displacement along different directions is processed by modulus operation, and the obtained remainder is associated with firing rate of grid cell. Compared with the original model, the improved parts include that: the base of modulus operation is changed, and the firing rate in firing field is encoded by Gaussian-like function. Simulation validates that the firing pattern generated by the improved computational model is more consistent with biological characteristic than original model. Besides, the firing pattern is badly influenced by the cumulative positioning error, but the computational model can also generate the regularly hexagonal firing pattern when the real-time positioning results are modified. 相似文献
网格计算作为分布式计算在科学计算领域的发展方向,可以为对地观测数据的处理提供强大的计算力。在分析遥感信息服务网格节点(Remote Sensing Information Service Grid Nodes,RSSN)中网络数据传输和负载均衡两个关键问题的基础上,提出了一种有效的基于游程编码和Huffman编码的数据压缩方法和基于"计算端元"的任务分配策略,该方法针对遥感影像特点进行有效数据压缩,具有较好的压缩比,达到了17%,且能实现任务负载均衡。并在遥感信息服务网格节点计算平台上,以中国范围内1km分辨率气溶胶光学厚度(Aerosol Optical Depth,AOD)反演计算为例,从压缩率和计算时间效率方面验证和分析了上述方法的有效性。 相似文献
Smart transportation has a significantly impact on city management and city planning, which has received extensive attentions from academic and industrial communities. Different from omni-directional sensing system, as a directional sensing system, the multimedia-directional sensor network holds the special coverage scheme, which is usually used for smart cities, smart transportation, and harsh environment surveillance, for instance, nuclear-pollution regions where are inhospitable for people. This paper advances Virtual Stream Artificial Fish-swarm based Coverage-Enhancing Algorithm (VSAFCEA) as a coverage-enhancing means in multimedia directional sensor networks. Firstly, a concept of virtual streams, based on traditional artificial fish-swarm algorithm, is proposed. Then, the traditional behaviors of fishes in artificial fish-swarm algorithm are modified and expanded with several new behaviors. Finally, the presented VSAFCEA is adopted for coverage-enhancing issue in the situation of directional sensor networks with rotational direction-adjustable model. With a sequence of steps of artificial fishes in virtual stream, the presented VSAFCEA can figure out the approximation to the highest area coverage rate. Based on comparison of these simulation results (results of presented VSAFCEA and that of other typical coverage-enhancing ways in directional sensor networks), the conclusion can be drawn that VSAFCEA could attain higher area coverage rate of directional sensor networks with fewer iterative computing times.