Randn

The file calculates and plots FM noise sidebands for a carrier. It also does sinusoidal modulation. This simple way of adding noise to a carrier is useful for simulation of PLLs. It turns out, though, that the mean of the randn function is not as close to zero as it could be, and this causes the... Platforms: Matlab

Fast Algorithm estimating the number of sinusoids in a white Gaussian noise. This algorithm use a sub-space method based on chi-square statistics of eigen values of the Autocorrelation Matrix.Example :clear, close all hiddenN = 512;L_vrai = 4;fe = 2000;F = (0:(fe/2)/(N/2-1):(fe/2));snr = [-10 -10... Platforms: Matlab

Some curve fitting or smoothing tools can benefit from knowledge of the noise variance to expect on your data. Kalman filters use this information, also some spline fitting tools. So I wrote a function to extract the noise variance from a signal vector. It also works on any specified dimension of... Platforms: Matlab

To compute the Euclidean separation (L2 norm) between two sets of points in MATLAB can be slow and/or memory-hungry. In some cases (most particularly, if you are working with 2D, 3D or 4D data), this function will do it 2-4 times faster than the fastest m-code I've seen (due to Germano Gomes) and... Platforms: Matlab

The result will be displayed in a matrix format.For uniform distributions,the values returned by the MATLAB function rand() are multiplied by (b-a), then added to a.For normal distributions the output of randn() is multiplied by the standard deviation (b), and then added to the desired to the... Platforms: Matlab

The result will be displayed in a matrix format. For uniform distributions,the values returned by the MATLAB function rand() are multiplied by (b-a), then added to a.For normal distributions the output of randn() is multiplied by the standard deviation (b), and then added to the desired to the... Platforms: Windows, Mac, *nix, Matlab, BSD Solaris

LLR_DEMOD LLR Demodulator H = LLR_DEMOD_MEX(CONSTELLATION, MAPPING, METHOD) constructs a LLR demodulator object H for a given constellation, mapping and noise variance. The vectors CONSTELLATION and MAPPING are usually generated by using MATLAB Modem Modulation Modem. and contain the complex or... Platforms: Matlab

The gradient function in Matlab allows you to compute the slope of a curve along its entire length. But if your curve is a noisy one, then gradient will also be noisy. In this event one might desire to fit a moderately low order polynomial regression model in a sliding window, then differentiate... Platforms: Matlab

This is a very simple function to find the local maximum in any dimensional array. As simple as it is it still gives nice results.I use the imdilate() function as a maximum operation and then compare the data to the result.The function receives three parameters:the data, a vector defining the... Platforms: Matlab

FASTRMS Instantaneous root-mean-square (RMS) power via convolution.FASTRMS(X), when X is a vector, is the time-varying RMS power of X, computed using a 5-point rectangular window centered at each point in the signal. The output is the same size as X and contains, for each point in X, an estimate... Platforms: Matlab

Suppose that you have a signal Y (Y can be a time series, a parametric surface or a volumetric data series) corrupted by a Gaussian noise with unknown variance. It is often of interest to know more about this variance. EVAR(Y) thus returns an estimated variance of the additive noise.EVAR provides... Platforms: Matlab

function P=ipeak(DataMatrix,PeakD,AmpT,SlopeT,SmoothW,FitW)Keyboard-operated Interactive Peak Finder for data in data matrix "DataMatrix", with x values in row 1 and y values in row 2. Returns the peak table in P (Peak #, Position, Height, Width.) See... Platforms: Matlab

B3MSV Bidirectional Branch and Bound(B3) subset selection using the the Minimum Singular Value (MSV) as the criterion.Consider the following subset selection problem:Given a tall (m x n, m>n) matrix, A, to find n rows of A such that the resulted n x n square submatrix has the largest MSV among... Platforms: Matlab

The function The LMFnlsq.m serves for finding optimal solution of an overdetermined system of nonlinear equations in the least-squares sense. The standard Levenberg- Marquardt algorithm was modified by Fletcher and coded in FORTRAN many years ago (see the Reference). This version of LMFnlsq is... Platforms: Matlab

The conjugate gradient method aims to solve a system of linear equations, Ax=b, where A is symmetric, without calculation of the inverse of A. It only requires a very small amount of membory, hence is particularly suitable for large scale systems.It is faster than other approach such as Gaussian... Platforms: Matlab

[blockVectorX,lambda]=lobpcg(blockVectorX,operatorA)outputs the array of algebraic smallest eigenvalues lambda andcorresponding matrix of orthonormalized eigenvectors blockVectorX of the Hermitian (full or sparse) operator operatorA using input matrix blockVectorX as an initial guess, without... Platforms: Matlab

easyfitGUI(varargin) fits real data Y = f(X) easyfitGUI open a figure with uimenus devoted to process the data. VARARGIN: one or several matrix [X, Y] having: first column = vector of the independant variable (X) second column = vector of the dependant variable (Y). The Y-data are plotted... Platforms: Matlab

anneal Minimizes a function with the method of simulated annealing (Kirkpatrick et al., 1983) ANNEAL takes three input parameters, in this order:LOSS is a function handle (anonymous function or inline) with a loss function, which may be of any type, and needn't be continuous. It does, however,... Platforms: Matlab

mPlot is an enhanced plotting engine that extends the basic plotting functionality delivered with Matlab. The purpose of mPlot is to consolidate daily plotting and formatting tasks into a single, easy-to-use object. Provided within the class are both high-level and low-level functionality. The... Platforms: Matlab