Satisficing search algorithms for selecting near-best bases in adaptive tree-structured wavelet transforms
Satisficing search algorithms for selecting near-best bases in adaptive tree-structured wavelet transforms
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DOI：
10.1109/78.539028
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发表时间：
1996-10
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影响因子：
--
通讯作者：
C. Taswell
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文献类型：
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作者：
C. Taswell
提出了在冗余树结构小波变换中自适应选择近最佳基和近最佳帧分解的满意搜索算法。各种加性或非加性信息成本函数中的任何一个都可以用作在搜索树时比较和选择节点的决策标准。该算法适用于由任何类型的小波生成的树结构变换，无论是正交、双正交还是非正交。这些令人满意的搜索算法实现了次优化而不是优化原则，并获得了降低计算复杂性以及显着节省内存、触发器和时间的重要优势。尽管是次优方法，但在某些重要且实际的情况下，可以考虑使用可产生接近最佳基础的可加性或非可加成本的自上而下的树搜索算法，该算法比可产生最佳基础的可加性成本的自下而上的树搜索算法更好。这里，“优于”意味着，实际上，相对部分的计算工作可以获得相同水平的性能。针对真实语音的数据压缩和人工瞬态的时频分析，展示了比较各种信息成本函数和基础选择方法的实验结果。
Satisficing search algorithms are proposed for adaptively selecting near-best basis and near-best frame decompositions in redundant tree-structured wavelet transforms. Any of a variety of additive or nonadditive information cost functions can be used as the decision criterion for comparing and selecting nodes when searching through the tree. The algorithms are applicable to tree-structured transforms generated by any kind of wavelet whether orthogonal, biorthogonal, or nonorthogonal. These satisficing search algorithms implement suboptimizing rather than optimizing principles, and acquire the important advantage of reduced computational complexity with significant savings in memory, flops, and time. Despite the suboptimal approach, top-down tree-search algorithms with additive or nonadditive costs that yield near-best bases can be considered, in certain important and practical situations, better than bottom-up tree-search algorithms with additive costs that yield best bases. Here, "better than" means that, effectively, the same level of performance can be attained for a relative fraction of the computational work. Experimental results comparing the various information cost functions and basis selection methods are demonstrated for both data compression of real speech and time-frequency analysis of artificial transients.