Ultrasound images suffer of multiplicative noise named speckle. Bayesian shrinkage in transform domain is a well-known method based on finding threshold value to suppress the speckle noise. The main problem of applying Bayesian shrinkage is finding the optimum threshold value in appropriate transform domain. In this paper, we compare the performance of adaptive Bayesian thresholding when nonsub...

PURPOSE Alcohol consumption can lead to risky driving and increase the frequency of traffic accidents, injuries and mortalities. The main purpose of our study was to compare simulated driving performance between two groups of drivers, one consumed alcohol and the other not consumed, using a systematic review. METHODS In this systematic review, electronic resources and databases including Medl...

—The so-called constrained least mean-square algorithm is one of the most commonly used linear-equality-constrained adaptive filtering algorithms. Its main advantages are adaptability and relative simplicity. In order to gain theoretical insights into the performance of this algorithm, we examine its mean-square convergence and derive an expression for its steady-state mean-square deviation. Ou...

—The so-called constrained least mean-square algorithm is one of the most commonly used linear-equality-constrained adaptive filtering algorithms. Its main advantages are adaptability and relative simplicity. In order to gain analytical insights into the performance of this algorithm, we examine its mean-square performance and derive theoretical expressions for its transient and steady-state me...

Spurred by an experimental controversy in the literature, we investigate the end-monomer dynamics of semiflexible polymers through Brownian hydrodynamic simulations and dynamic mean-field theory. Precise experimental observations over the last few years of end-monomer dynamics in the diffusion of double-stranded DNA have given conflicting results: one study indicated an unexpected Rouse-like sc...

We consider the convergence analysis of the sign algorithm for adaptive filtering when the input processes are uncorrelated and Gaussian. Asymptotic time-averaged convergence results for the mean deviation error, mean-square deviation error, and for the signal estimation error are established. These results are shown to hold for arbitrary step size μ > 0.