A simple method for smoothing noisy data is to use a moving average. The original data is partitioned into overlapping sets of a given sample size, typically by shifting along one step at a time. The new smoothed data is made by computing the average for each of the sets. Larger sample sizes result in greater smoothing. Using the median of the sample sets gives a moving median for the data and produces different smoothing effectsComponente Curricular::Ensino Médio::Matemátic
This paper studies nonparametric regression using smoothing splines. It proposes a method that combi...
Taking some form of moving averages yields a smoothing of time series which is delayed. However, tak...
A Monte-Carlo weighted moving average procedure was developed for smoothing time series data. The ap...
A simple method for smoothing noisy data is to use a moving average. The original data is partitione...
Kernel smoothing refers to a general methodology for recovery of underlying structure in data sets. ...
<p><i>N</i> denotes the number of ensembles used for averaging. The resulting waveform from ensemble...
SIGLEAvailable from British Library Document Supply Centre- DSC:0678.231F(AD-A--195671)(microfiche) ...
Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics. Thesis. 1967. Sc.D.MIC...
Smoothing or filtering of data is first preprocessing step for noise suppression in many application...
Two Tukey’s techniques which are resistant line for linear trend and resistant smoothing for non li...
The statistical range was substituted for the variance in local noise smoothing algorithms proposed ...
This thesis presents a method for smoothing data based on local procedures. The method attempts to r...
[[abstract]]©1991 SPIE - In this paper we describe a novel noise smoothing method based on a nonpara...
We consider the problem of converting a set of numeric data points into a smoothed approximation oft...
(A) A raw confocal image of an intermediate cell layer, with gross segmentation to remove extraneous...
This paper studies nonparametric regression using smoothing splines. It proposes a method that combi...
Taking some form of moving averages yields a smoothing of time series which is delayed. However, tak...
A Monte-Carlo weighted moving average procedure was developed for smoothing time series data. The ap...
A simple method for smoothing noisy data is to use a moving average. The original data is partitione...
Kernel smoothing refers to a general methodology for recovery of underlying structure in data sets. ...
<p><i>N</i> denotes the number of ensembles used for averaging. The resulting waveform from ensemble...
SIGLEAvailable from British Library Document Supply Centre- DSC:0678.231F(AD-A--195671)(microfiche) ...
Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics. Thesis. 1967. Sc.D.MIC...
Smoothing or filtering of data is first preprocessing step for noise suppression in many application...
Two Tukey’s techniques which are resistant line for linear trend and resistant smoothing for non li...
The statistical range was substituted for the variance in local noise smoothing algorithms proposed ...
This thesis presents a method for smoothing data based on local procedures. The method attempts to r...
[[abstract]]©1991 SPIE - In this paper we describe a novel noise smoothing method based on a nonpara...
We consider the problem of converting a set of numeric data points into a smoothed approximation oft...
(A) A raw confocal image of an intermediate cell layer, with gross segmentation to remove extraneous...
This paper studies nonparametric regression using smoothing splines. It proposes a method that combi...
Taking some form of moving averages yields a smoothing of time series which is delayed. However, tak...
A Monte-Carlo weighted moving average procedure was developed for smoothing time series data. The ap...