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A theory is developed for quantifying fault detectability and fault isolability properties of static linear stochastic models. Based on the model, a stochastic characterization of system behavior in different fault modes is defined and a general measure, based on the Kullback-Leibler information, is proposed to quantify the difference between the modes. This measure, called distinguishability, of...
In this paper, for statistical validation of rival (analytical or simulation) models collected for modeling observable process in stochastic system (say, transportation or service system), a uniformly most powerful invariant (UMPI) test is developed from the generalized maximum likelihood ratio (GMLR). This test can be considered as a result of a new approach to solving the Behrens-Fisher problem...
Non-homogeneous Poisson process (NHPP) models are widely used for repairable system analysis. Different NHPP models have been developed for different applications. It has been noticed that almost all the existing models apply only a single model for the entire system development or operation period. However, in some circumstances, such as when the system design or the system operation environment...
This paper proposes a new approach to analyze crosstalk of coupled interconnects in the presence of process variations. The suggested method translates correlated process variations into orthogonal random variables by principle component analysis (PCA). combined with polynomial chaos expression (PCE), the technique utilizes Stochastic Collocation Method (SCM) to analyze the system response of coupled...
In this paper, we address the problem of orthogonal frequency-division multiplexing (OFDM) channel estimation in the presence of phase noise (PHN) and carrier frequency offset (CFO). In OFDM systems, PHN and CFO cause two effects: the common phase error (CPE) and the intercarrier interference (ICI) which severely degrade the accuracy of the channel estimate. In literature, several algorithms have...
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