Linear minimum mean square error (LMMSE) estimation is often ill-conditioned, suggesting that unconstrained minimization of the an inadequate approach to filter design. To address this, we first develop a unifying framework for studying constrained LMMSE problems. Using this framework, explore important structural property filters involving certain prefilter. Optimality invariant under invertib...

Measurement of the quality of image compression is important for image processing application. In this paper, we propose an objective image quality assessment to measure the quality of gray scale compressed image, which is correlation well with subjective quality measurement (MOS) and least time taken. The new objective image quality measurement is developed from a few fundamental of objective ...

We consider a univariate semimartingale model for (the logarithm of) an asset price, containing jumps having possibly infinite activity (IA). The nonparametric threshold estimator ˆ IV n of the integrated variance IV := ∫ T 0 σ sds proposed in [6] is constructed using observations on a discrete time grid, and precisely it sums up the squared increments of the process when they are under a thres...

Abstract. The root-mean-squared error (RMSE) and mean absolute (MAE) are widely used metrics for evaluating models. Yet, there remains enduring confusion over their use, such that a standard practice is to present both, leaving it the reader decide which more relevant. In recent reprise 200-year debate Willmott Matsuura (2005) Chai Draxler (2014) give arguments favoring one metric or other. How...