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基于小波变换的图象编码中的噪声分析和优化比特分配 被引量:8
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作者 李涛 俞斯乐 《中国图象图形学报(A辑)》 CSCD 1997年第8期549-554,共6页
研究了基于小波变换的图象编码。在系统地分析了小波变换各子图象的量化噪声和恢复噪声的基础上,提出了在给定的比特率下,使系统恢复失真达到最小的优化比特分配方案。指出了在均匀量化时各子图象量化步长之间具有成倍的关系。模拟实... 研究了基于小波变换的图象编码。在系统地分析了小波变换各子图象的量化噪声和恢复噪声的基础上,提出了在给定的比特率下,使系统恢复失真达到最小的优化比特分配方案。指出了在均匀量化时各子图象量化步长之间具有成倍的关系。模拟实验证明了该结论,并给出了满意的结果。 展开更多
关键词 小波变换 噪声分析 优化特分配 图象编码
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Research on Optimized Allocation of English Teaching Resources Based on Network Cloud Platform
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作者 LIU Yajuan 《International English Education Research》 2018年第1期73-76,共4页
The allocation of resources in English teaching can improve the ability of resource sharing, in order to optimize the allocation of resources, so as to improve the performance of English teaching, and promote the cons... The allocation of resources in English teaching can improve the ability of resource sharing, in order to optimize the allocation of resources, so as to improve the performance of English teaching, and promote the construction of English teaching resources database, a method of optimizing the allocation of English teaching resources is proposed based on network cloud platform. Text semantic key words conceptual decision tree model is constructed for massive English teaching resources allocation, semantic information conversion method is used to compute key semantic features of English Teaching resources, the concept convergence point of English Teaching resource allocation is formed in semantic model. According to the set between the upper and lower relationship, a decision tree model of English Teaching semantic subject words is constructed, semantic conversion and information extraction are realized. English teaching resources optimization allocation simulation is taken in the cloud platform, simulation results show that the scheduling performance of English teaching resources is better, and the adaptive allocation ability of English teaching resources is stronger, and the resource utilization rate is higher. 展开更多
关键词 Network cloud platform English teaching resources Allocation: Decision tree model
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