REAK: Reliability analysis through Error rate-based Adaptive Kriging

Adaptive Least Error Rate

Least Bit Error Rate Adaptive

Modified Bayesian Kriging for Noisy Response Problems for Reliability Analysis

This paper develops a new modified Bayesian Kriging (MBKG) surrogate modeling method for problems in which simulation analyses are inherently noisy and thus standard Kriging approaches fail to properly represent the responses. The purpose is to develop a method that can be used to carry out reliability analysis to predict probability of failure. The formulation of the MBKG surrogate modeling me...

Adaptive Minimum Bit-Error-Rate Filtering

Adaptive filtering has traditionally been developed based on the minimum mean square error (MMSE) principle and has found ever-increasing applications in communications. The paper develops adaptive filtering based on an alternative minimum bit error rate (MBER) criterion for communication applications. It is shown that the MBER filtering exploits the non-Gaussian distribution of filter output e...

Estimating the Bayes Error Rate through Classi

The Bayes error provides the lowest achievable error rate for a given pattern classiication problem. There are several classical approaches for estimating or nd-ing bounds for the Bayes error. One type of approach focuses on obtaining analytical bounds, which are both diicult to calculate and dependent on distribution parameters that may not be known. Another strategy is to estimate the class d...