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In this study, the effects of adding independent noise to observations of a suboptimal detector are studied for M-ary hypothesis-testing problems according to the minimax criterion. It is shown that the optimal additional noise can be represented by a randomization of at most M signal values under certain conditions. In addition, a convex relaxation approach is proposed to obtain an accurate approximation...
Performance of some suboptimal detectors can be improved by adding independent noise to their observations. In this paper, the effects of adding independent noise to observations of a detector are investigated for binary composite hypothesis-testing problems in a generalized Neyman-Pearson framework. Sufficient conditions are derived to determine when performance of a detector can or cannot be improved...
Under certain conditions, addition of noise can enhance performance of suboptimal detectors, which is called the stochastic resonance (SR) effect. In this paper, the effects of SR are investigated for conventional detectors in the presence of multiple-access interference. First, conditions under which probability of error performance of the detector can or cannot be improved are obtained. Then, performance...
In this paper, mean acquisition time (MAT) analysis of fixed-step serial search (FSSS) algorithms is presented. First, it is shown that the MAT of an FSSS algorithm can be obtained from that of a conventional serial search (CSS) algorithm after a certain mapping of the uncertainty region. Then, a generic formula for the MAT of FSSS algorithms is derived, which is valid for both dense and sparse channel...
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