matlab parameter estimation

Results 41 to 50 of about 50 results found for 'matlab parameter estimation' open source codes and projects!

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Optimization Algorith for Uncertain Nonlinear Dynamic System

dynamic integrated system optimization and parameter estimation (disope) technique. disope + momentum + partan algorithm to improve convergence of a nonlinear dynamic system. study covers application for chemical process industries, robotics, genomics, etc. matlab 6.5 (r13) advanced process control,

http://www.mathworks.com/matlabcentral/fileexchange/28364

Truncated Lognormal Estimation

parameter estimation of unknown left truncated lognormal. [mu, sigma, d] = trunclognormest(data) returns the estimated parameters of the lognormal distribution, with unknown left truncation,

http://www.mathworks.com/matlabcentral/fileexchange/27791

ECC Image alignment algorithm

which is by far the most common case. due to gradient information, ecc algorithm achieves high accuracy in parameter estimation (i.e. subpixel accuracy).

http://www.mathworks.com/matlabcentral/fileexchange/27253

Two-Sided Power Distribution

van dorp, j.r. and s. kotz. 2002. a novel extension of the triangular distribution and its parameter estimation. the statistician, 51: 63-79. matlab 7 (r14) twosided power distribution probability simulation .

http://www.mathworks.com/matlabcentral/fileexchange/16368

OptiPt

features of optipt are:. -- easy model specification. -- high-precision parameter estimation. -- goodness of fit test. -- covariance matrix of the parameter estimates. reference:. wickelmaier, f. & schmid, c. (2004).

http://www.mathworks.com/matlabcentral/fileexchange/4862

marocewod

(2) principal factor method; (3) iterated principal factor method, and (4) maximum likelihood method. the two most popular methods of parameter estimation are the principal component and the maximum likelihood method.

http://www.mathworks.com/matlabcentral/fileexchange/10739

anfactpcwod

(2) principal factor method; (3) iterated principal factor method, and (4) maximum likelihood method. the two most popular methods of parameter estimation are the principal component and the maximum likelihood method.

http://www.mathworks.com/matlabcentral/fileexchange/10602

maroce

(2) principal factor method; (3) iterated principal factor method, and (4) maximum likelihood method. the two most popular methods of parameter estimation are the principal component and the maximum likelihood method.

http://www.mathworks.com/matlabcentral/fileexchange/10738

anfactpc

(2) principal factor method; (3) iterated principal factor method, and (4) maximum likelihood method. the two most popular methods of parameter estimation are the principal component and the maximum likelihood method.

http://www.mathworks.com/matlabcentral/fileexchange/10601

Parameter Estimation Technique for general datasets

an estimation procedure for many types of data. 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

http://www.mathworks.com/matlabcentral/fileexchange/29669

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