GAUSSian REALIZation of a random variable with standard deviation sigma and correlation length lambda
A recursive implementation of the Gaussian filter. This implementation yields an infinite impulse response filter that has 6 MADDs per dimension independent of the value of sigma in the Gaussian kernel.
Recursive Gabor filtering for 1D...
% the water-filling process % x: a vector with each component representing noise power % P: total power % % The returned vector p maximizes the total sum rate given by % sum(log(1 + p./x)), subject to the power constraint...
This M-file focuses on a 3-class pattern classification problem. It generates hundred random samples for each pattern class using given parameters for the class-conditional densities. Further the Gaussian classifier is implemented to classify test...
This toolkit has two main purposes.
1. Decomposition and visualization of paraxial beams in Hermite-Gaussian and Laguerre-Gaussian bases. (These functions are located in the subdirectory "transverse.")
2....
This function segments (clusters) an image into object classes, and estimates and corrects for slow varying illumination artifacts. Estimates and corrects for bias field in 3D MRI, streak artifacts in CT, and illumination artifacts in color...
This program is a very basic three-dimensonal FDTD program with a source in the middle of the problem space.This similar to the two dimensonal problem but here we assume that the source is not a point source. A simple Dipole Antenna consists...
The Radial Basis Function (RBF) with LMS algorithm for Simulink. The Radial Basis Function (RBF) Batch-mode training Fixed centers selected at random The Gaussian basis functions Computing the output weights with LMS...
Errors in bar series are traditionally represented using error bars. However these give a poor visual fix on the data. By fading the bar rather than representing an error by a fixed-length bar, we better represent the uncertainty in the data. In...
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...
This script calculates BER for a numebr of SNR values in gaussian environment for QAM 16 Modulation.
It calculates 100 errors for each BER measuremnet for better results.
I hope this will be helpful for students of signal...
The Gaussian Kernel can be changed to any desired kernel. However such a change will not dramatically improve results. This is a variant of ridge regression using the kernel trick (Mercers Theorem).
G3 = gauss3D(sz_X, sz_Y, sz_Z, a, prec);
returns a 3 dimensional matrix being a gaussian bell curve where the width in the (x/y/z)-dimension is proportional to 1/a(1), 1/a(2) and 1/a(3), respectively. "prec" is the data...
SMIProm: Single Molecule Image Processing Program. I use this program to get intensity profiles of single molecule images and fit it using the curve fitting toolbox. basically you can use the program to: -->Select an ROI from an...
Compute the solution to Hallen's Integral Equation with symmetric excitation using pulse basis functions and point matching. Assumes a straight wire along z-axis.
Uses the following script for gaussian quadrature weights:
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...
Simulation of a gaussian pulse propagated in free space through 1000 um, using finite differences. Just run the script and you'll get a surface which is made up of the pulse propagated at 1 um steps.
Non-parametric regression is widely used in many scientific and engineering areas, such as image processing and pattern recognition.
Non-parametric regression is about to estimate the conditional expectation of a random variable:
A uniform random number generator is used to generate the binary information sequence from the binary data source. The sequence of d-de?0d-deOaos and d-de?1d-deOaos is mapped into sequence of +E and d-deOCtE where E represents the signal...
This is an implementation of fast bilateral filtering for 3D images. This filter smoothes the image while preserving edges, but in its most straightforward implementation is very computationally demanding, especially with large 3D images. Fast... |