Nonlinear Correlation

Particle swarm optimization is a derivative-free global optimum search algorithm based on the collective intelligence of a large group of intercommunicating entities. The individual particles are simple and primitive, knowing only their own current locations and fitness values, their personal...

We use the power of symbolic toolbox in order to find the optimal point in an arbitrary multivariate functionChange the following code based on your objective function and run the programFunction F in Symbolic Formata='(x1^2+x2-11)^2+(x1+x2^2-7)^2';The code will iterate and converge to x and y of...

Three different nonlinear control algorithms are used to control a three degree of freedom PUMA560 robot. These algorithms are:Computed Torque Control, Sliding Mode and Backstepping Control.The robot dynamics are taken from:Brian Armstrong, Oussama Khatib & Joel Burdick , d-deDUThe Explicit...


Platforms: Matlab

The package contains a simulink model of a mechanism which verify the angle of the road and adjust the torques by giving a angle to a plate located under the load session.this model is not a very complicated one and would be useful to whom want to:1.get familiar with control designs specially PID...


Platforms: Matlab

Golden Section search for minimizing a nonlinear function in one dimensionDavidon-Fletcher-Powell (DFP) method. This is a method to solve an unconstrained nonlinear program


Platforms: Matlab

Single tank system nonlinear model was develop & finding the operating point of it using script file of the matlab with solving of ode for it and ploting the response


Platforms: Matlab

The proportional, integral and differential terms of PID control are modified by simple nonlinear terms, depending on the error.That makes the control faster, more precise and more robust.This was tested and proven at the control lab of the Munich University of Applied Science.


Platforms: Matlab

Develop a Matlab program to demonstrate a neural network autoassociative memory. Show the importance of using the pseudoinverse in reducing cross correlation matrix errors. Show the performance of the autoassociative memory in noise. The results are contained in the Matlab file assoc_mem_demo.m


Platforms: Matlab

This is a collection of functions I wrote for use of MATLAB with tree-ring time series. Functions are included for skeleton plotting, group time-series plotting, and correlation analysis of seasonal climatic time series with tree-ring indices ("tree-ring response-functions").


Platforms: Matlab

Uses fft to calculate the circular cross correlation of two periodic signal vectors.This is equivalent to xc(k)=sum(u1.*circshift(u2,k)), but much faster (on the order of 500 times faster for a 1024 point signal).The package also includes two examples. One checks the calculation against the...


Platforms: Matlab

This program performs a Monte Carlo simulation of a coherent QPSK communication system and plot the error probability performance over additive whit Gaussian noise channel. The detection is based on correlation metric. Simulation is performed for 10,000 bits and measurements are made accordingly.


Platforms: Matlab

DFT plays important role in DSP and used in wide variety of applications like correlation and spectral analysis. Understanding quantization errors in its computation is an important aspect of its design either for s/w or h/w implementation.A complex DFT of N points has N complex (4N real)...


Platforms: Matlab

A fast vectorized implementation of the ncc that handles color (3 channel) images as well as gray level.The algorithm for colored images is based on the ncc formulation for vector valued functions.Note: A bug that I found in the normxcorr2 was also fixed here.


Platforms: Matlab

Let us assume the following MIMO model:Y(k)=HX(k)+Y(k)This file can detect the number of sources, i.e the size of the vector X(k) from the received signal Y(k). The noise is assumed spatially white and the number of receivers must be strictly greater than the number of sources. For more details...


Platforms: Matlab

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

Features:1. the program calculates the matter power spectrum, temperature spectrum, polarisation- and cross-correlation spectrum of a curved or flat Friedman-Robertson-Walker universe.2. it calculates the age of the universe, sigma8 and the age of the first start formation.3. massless neutrino's,...


Platforms: Matlab

SIMPGRIDSEARCH Multi-dimensional unconstrained nonlinear minimization using grid search + Simplex method. X = SIMPGDSEARCH(OBJFUN,GDVALUES) returns a vector X that is a minimizer of the function described in OBJFUN (usually an m file: OBJFUN.M).See OBJFUN_DEMO.M for how to write an objective...


Platforms: Matlab

FitChiTool provides an interface similar to the Curve Fitting Toolbox to the fitChiSquare function.This allows you to perform fits using chi-square when measurement errors are known on linear or nonlinear models. It allows allows you to perform fits with multiple independent (more than one x)...


Platforms: Matlab

L-BFGS-B is a collection of Fortran 77 routines for solving nonlinear optimization problems with bound constraints on the variables. One of the key features of the nonlinear solver is that the Hessian is not needed. I've designed an interface to the L-BFGS-B solver so that it can be called like...


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