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Multi-Objective Operator for Optimal Compression and De-compression of Random Signals

机译:多目标算子用于随机信号的最佳压缩和解压缩

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摘要

New multi-objective operators of random signals are presented in this paper. The new operators improve, under a unrestrictive condition, the performance of known techniques: the generalized Karhunen-Loéve transform, the transform considered by Brillinger and the generalized Brillinger-like transform. This is obtained by particular design of new operators which have more parameters to optimize than that of other operators described in literature.
机译:本文提出了一种新的随机信号多目标算子。新的算子在不受限制的条件下改善了已知技术的性能:广义的Karhunen-Loéve变换,Brillinger考虑的变换和广义的Brillinger变换。这是通过对新算子进行特殊设计而获得的,该算子比文献中描述的其他算子具有更多的参数要优化。

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