Exponential smoothing technique is one of the most important quantitative techniques in forecasting. The accuracy of forecasting of this technique depends on exponential smoothing constant. Choosing an appropriate value of exponential smoothing constant is very crucial to minimize the error in forecasting. This paper addresses the selection of optimal value of exponential smoothing constant to ...

This paper treats the least-squares linear smoothing problem for signal estimation using measurements contaminated by additive white noise correlated with the signal, with stochastic delays. We derive a general smoothing equation which is applied to obtain specific smoothing algorithms, which are referred in the signal estimation literature as fixed-point, fixed-interval, and fixed-lag smoothin...

BACKGROUND CT perfusion images have a high contrast ratio between voxels representing different anatomy, such as tissue or vessels, which makes image segmentation of tissue and vascular regions relatively easy. However, grey and white matter tissue regions have relatively low values and can suffer from poor signal to noise ratios. While smoothing can improve the image quality of the tissue regi...

2 Proofs for the Poisson model 3 2.1 Bounds for general linear estimators . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.2 Negative result for truncated Good-Toulmin estimator . . . . . . . . . . . . . . . . . 5 2.3 Bounds on SGT estimators: arbitrary smoothing . . . . . . . . . . . . . . . . . . . . 5 2.4 Poisson smoothing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...

We propose a new class of non-linear image recovery operators based on local smoothing applied both in the spatial domain (horizontal smoothing) and in the gray-level domain (vertical smoothing). The commonly used horizontal smoothing gives the way of reducing the noise level (noise filtering), whereas the vertical smoothing yields the edge preservation property. The method is indexed by a real...