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For Piecewise Smooth Signals, L1 Method Is The Best Among Lp: An Interval-Based Justification Of An Empirical Fact, Vladik Kreinovich, Arnold Neumaier
For Piecewise Smooth Signals, L1 Method Is The Best Among Lp: An Interval-Based Justification Of An Empirical Fact, Vladik Kreinovich, Arnold Neumaier
Departmental Technical Reports (CS)
Traditional engineering techniques use the Least Squares method (i.e., in mathematical terms, the l2-norm) to process data. It is known that in many practical situations, lp-methods with p=/=2 lead to better results. In different practical situations, different values of p are optimal. It is known that in several situations when we need to reconstruct a piecewise smooth signal, the empirically optimal value of p is close to 1. In this paper, we provide a new interval-based theoretical explanation for this empirical fact.
Interval-Based Robust Statistical Techniques For Non-Negative Convex Functions With Application To Timing Analysis Of Computer Chips, Michael Orshansky, Wei-Shen Wang, Gang Xiang, Vladik Kreinovich
Interval-Based Robust Statistical Techniques For Non-Negative Convex Functions With Application To Timing Analysis Of Computer Chips, Michael Orshansky, Wei-Shen Wang, Gang Xiang, Vladik Kreinovich
Departmental Technical Reports (CS)
In chip design, one of the main objectives is to decrease its clock cycle; however, the existing approaches to timing analysis under uncertainty are based on fundamentally restrictive assumptions. Statistical timing analysis techniques assume that the full probabilistic distribution of timing uncertainty is available; in reality, the complete probabilistic distribution information is often unavailable. Additionally, the existing alternative of treating uncertainty as interval-based, or affine, is limited since it cannot handle probabilistic information in principle. In this paper, a fundamentally new paradigm for timing uncertainty description is proposed as a way to consistently and rigorously handle partially available descriptions of …