1. X-Z identity 2 1.1. Notation 2 1.2. XZ identities 3 1.3. Some estimates 4 2. Orthogonal Telescope Decomposition 6 2.1. Properties and Assumptions 6 2.2. Convergence 8 3. Approximation and Smoothing Property 8 3.1. High frequency 9 3.2. Approximation property 9 3.3. Smoothing property 9 3.4. Smoothing property of popular smoothers 10 3.5. Convergence 11 4. Stable Decomposition and Quasi-Ortho...

Whenever a new mesh smoothing algorithm is introduced in the literature, initial experimental analysis is often performed on relatively simple geometric domains where the meshes need little or no element size grading. Here, we present a comparative study of a large number of well-known smoothing algorithms on triangulations of complex geometric domains. Our study reveals the limitations of some...

In the language modeling approach to information retrieval, Dirichlet prior smoothing frequently outperforms Jelinek-Mercer smoothing. Both Dirichlet prior and Jelinek-Mercer are forms of linear interpolated smoothing. The only difference between them is that Dirichlet prior determines the amount of smoothing based on a document’s length. Our hypothesis was that Dirichlet prior’s performance ad...

In this paper we introduce a video smoothing algorithm for MPEG compressed live video. This algorithm, called Pattern Smoothing, transmits compressed video via both Constant Bit Rate (CBR) and Variable Bit Rate (VBR) channels. In order to take advantage of the gains achieved through statistical multiplexing of multiple sources over a single link, this algorithm utilizes a CBR channel to reduce ...

Figure 2: Simulated (left) and in vivo (right) ADC point estimates without adaptive smoothing (a and e) and with adaptive smoothing (b and f). ADC uncertainties with adaptive smoothing (c and g) and without adaptive smoothing (d and h). On all maps with adaptive smoothing, the borrowing strength is shown by a border around each pixel; bright lines indicate strong borrowing; dark lines indicate ...

A popular smoothing technique commonly used in time series analysis is double exponential smoothing. Basically, it’s an improvement of simple exponential smoothing which does the exponential filter process twice. Many researchers had developed the technique, hence Brown’s double exponential smoothing and Holt’s double exponential smoothing. Here, we introduce a new approach of double exponentia...

An approach to multi-dimensional smoothing is introduced which is based on a penalized with a modified The choice of penalty stanaard multi-dim~nsiQnal.Lapladan SQ11aI'e errQrcharacteristics at-least on the interior of hyper-rectangular~omains, which has wide restorationproblems,computar tions are carried out using fast Fourier transforms. Non-linear smoothing is accomplished by iterative appli...

BACKGROUND Speckle Tracking Echocardiography (STE) strain analysis relies on both spatial and temporal smoothing. The user is often allowed to adjust these smoothing parameters during analysis. This experimental study investigates how different degrees of user controllable spatial and temporal smoothing affect global and regional STE strain values in recordings obtained from normal and ischemic...

Wavelets are explored as a data smoothing (or de-noising) option for solution monitoring data in nuclear safeguards. In wavelet-smoothed data, the Gibbs phenomenon can obscure important data features that may be of interest. This paper compares wavelet smoothing to piecewise linear smoothing and local kernel smoothing, and illustrates that the Haar wavelet basis is effective for reducing the Gi...

We examine the performance of Total Variation (TV) smoothing for processing of noisy Electrocardiogram (ECG) recorded by an ambulatory device. The TV smoothing is compared with traditionally-used bandpass filtering using ECG with artificially added noise, as well as with real-world noise obtained during physiological monitoring. The fundamental difference between TV smoothing and traditional ba...