Mean Comebacks

This could be very useful model when used in signal processing. I have implemented this to filter the disturbances in my ADC signals in my programming and it works good.

we had generated a signal and the we generated a random noise and add it to the signal,,then my using the lms algorithm we tried to cancel the effect of the noise on the signal and have the original signal back pure as possible

Mean or standard deviation are usually computed for whole part of the analysed signal. However, sometimes we would like to know how this quantities are changing in the data flow. MEANSTDF compute the expected mean and standard deviation values using user defined window for every data position....


Platforms: Matlab

For vectors, Y = RUNMEAN(X,M) computes a running mean (also known as moving average) on the elements of the vector X. It uses a window of 2*M+1 datapoints. M an positive integer defining (half) the size of the window. In pseudo code: Y(i) = sum(X(j)) / (2*M+1), for j = (i-M):(i+M), and...


Platforms: Matlab

Given mean anomaly and eccentricity of an orbit, eccentric anomaly can be calculated using Kepler's Equation. However, the equation is nonlinear, and an iterative technique must be used. This program uses a fixed-point iterative technique to output eccentric anomaly to a user defined tolerance,...


Platforms: Matlab

MATLAB implementation of IGRF11 fortran code as function for calculating Earth mean magnetic field. Implementation has been modified to default to GPS reference coordinates with output B components North, East, and Vertical. Spherical harmonic coefficients are derived from downloaded Excel...


Platforms: Matlab

function [optN, C, N] = sshist(x,N) [optN, C, N] = sshist(x,N) Function `sshist' returns the optimal number of bins in a histogram used for density estimation. Optimization principle is to minimize expected L2 loss function between the histogram and an unknown underlying density function. An...


Platforms: Matlab

Demo graphical user interface that finds an unconstrained mean-variance efficient frontier given asset price data. This data can come from Yahoo finance, where you can find the optimial portfolio for any set of assets you choose, or from a supplied Microsoft Access database.


Platforms: Matlab

Three factors interfere in the determination of pellet mean size. These are the impeller speed, the binding solution and the pelletization time. We use experimental design (Doehlert design) to predict pellet mean size versus the three factors. We determine the quadratic model by multi-linear...


Platforms: Matlab

- Subtracting the mean of the data from the original dataset - Finding the covariance matrix of the dataset - Finding the eigenvector(s) associated with the greatest eigenvalue(s) - Projecting the original dataset on the eigenvector(s) - Use only a certain number of the eigenvector(s) - Do...


Platforms: Matlab

Methods available:------------------Greatest Divisor : d'Hondt; Jefferson; Highest AverageSmallest Divisor : AdamsEqual Proportions : Huntington; Hill; Geometric MeanHarmonic Mean : DeanMajor Fractions : Sainte-Lague; Webster; Arithmetic Mean; Odd NumbersLargest Remainders : Vinton; Hamilton;...


Platforms: Matlab

This is an example of the basic Active Shape Model (ASM) and also the Active Appearance Model (AAM) as introduced by Cootes and Taylor, with multi-resolution approach, color image support and improved edge finding method. Very useful for automatic segmentation and recognition of biomedical...


Platforms: Matlab

In the paper "An estimation technique for Time Indexed gaussian Mixture Models", we propose a model specification that can be used to describe data with spikes, jumps, mean reversion, geometric brownian motion, you name it...We then develop an estimation procedures to extract the parameters from...


Platforms: Matlab

I was trying out modifications of the LMS algorithm so that it will converge faster and the mean square error will also be smaller. Getting to one of the drawbacks of LMS, that it has only one controllable parameter "mu", the selection of whose value will be the most critical from design point of...


Platforms: Matlab

Please see PORTOPTGADS, by following link 'Published m-files' below.PS. The cool picture is a visualization of Rastrigin's function, taken from Genetic Algorithm and Direct Search Toolbox documentation.


Platforms: Matlab

The radially averaged power spectrum (RAPS) is the direction-independent mean spectrum, i.e. the average of all possible directional power spectra. The radially averaged power spectrum provides a convenient means to view and compare information contained in 2-D spectra in 1-D. This function...


Platforms: Matlab

This m-file returns the mean, variance and standard deviation of the multinomial distribution with parameters N and P. The Expected Value (i.e., averages):Expected Value = m = Sum(Xi doOCo Pi), the sum is over all i's. Expected value is another name for the mean and (arithmetic) average.The...


Platforms: Matlab

ecdfcalc4fe calculates absic statistics for a sample set: mean, variance, std.dev, kurtosis, skewness, probability mass function/density funcion and cumulative distribution.it does not provide new algorithms but combines current function on the statistical toolbox to ease things a bitsimple to...


Platforms: Matlab

Estimates the exact statistical power of a performed Student's t test about mean(s). Here, according to Winer (1970) we use the exact power by the noncentral cumulative distribution function. It recalls you the statistical result of the test you should have arrived. Inputs:t - Student's t...


Platforms: Matlab

A common technique for removing noise from images is by blur-ring them with a weighted mean or a Gaussian filter. Through theseprocesses noise reduction is achieved, but unfortunately, valuableinformation is lost and the details of object boundaries aredeformed. A solution to this problem,...


Platforms: Matlab