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l(infinity)-Stability for linear multiresolution algorithms: A new explicit approach. Part I: The basic rules and the Daubechies case

机译:l(无限)-线性多分辨率算法的稳定性:一种新的显式方法。第一部分:基本规则和道伯奇斯案

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This general study is motivated by recent experiments showing that a multiresolution scheme without control in the infinity norm can produce numerical artifacts. This class of stability for the Mallat's multiresolution transform associated to orthogonal wavelet filters that belong to the class of linear multiresolution algorithms is revisited. Explicit error bounds in the infinity norm are presented by using an appropriate reformulation of the successive convolutions of a vector and assuming a contraction property. In the case of the decomposition an alternative normalization is necessary. We apply our general stability framework to the specific case of Daubechies' filters. The knowledge of explicit error bounds has some advantages in real problems as: industry applications, medical pathologies or FBI fingerprint compression. Our workable bounds give the level of compression necessary to recover the signal with a reconstruction error smaller than a prefixed tolerance. Our study presents two important aspects, the first one is the fact that we give precise error bounds and the second one is that we only use basic rules that can be understood for a wide part of the scientific community. Moreover, the results should be useful in mathematical, medical, physical, biological and engineering applications. (c) 2008 Elsevier Inc. All rights reserved.
机译:这项一般性研究受到最近的实验的启发,这些实验表明在无穷大范数内没有控制的多分辨率方案会产生数值伪像。再次探讨了与属于线性多分辨率算法类别的正交小波滤波器相关的Mallat多分辨率变换的稳定性。通过对向量的连续卷积进行适当的重构并假设其具有收缩性质,可以表示无穷大范数中的显式误差范围。在分解的情况下,需要进行替代的归一化。我们将一般稳定性框架应用于Daubechies过滤器的特定情况。明确的错误界限知识在实际问题中具有一些优势,例如:行业应用,医疗病理或FBI指纹压缩。我们的可行范围给出了以小于预定公差的重建误差恢复信号所需的压缩级别。我们的研究提出了两个重要方面,第一个方面是我们给出了精确的误差范围,第二个方面是我们仅使用了可以为科学界广泛理解的基本规则。此外,结果应在数学,医学,物理,生物学和工程应用中有用。 (c)2008 Elsevier Inc.保留所有权利。

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