Numerical software

Get computer hardware information on windows with wmic in matlab

The following Matlab project contains the source code and Matlab examples used for get computer hardware information on windows with wmic . wmicGetHardwareInfos queries informations about the computer hardware (OS, CPU, GPU, RAM, Disk) It displays results in the command window or in a text file. wmicGetHardwareInfos requires wmicGet (submission #47858 on the File Exchange).

Add multiple y-axes to plots, includes mods for zoom, pan, datatip and colorbar tools in r2013b. in matlab

The following Matlab project contains the source code and Matlab examples used for add multiple y-axes to plots, includes mods for zoom, pan, datatip and colorbar tools in r2013b. . Based on the excellent AddAxis 5 by Harry Lee, this package will allow you to use the MATLAB zoom, pan, and data cursor tools as of version R2013b (other versions untested).

My xminortick in matlab

The following Matlab project contains the source code and Matlab examples used for my xminortick. Syntax: my_XMinorTick Input: {opt} n_minortick - number of steps of XMinorTick [values (numeric)]                     five steps by default {opt} color - color used in XMinorTick, black by default {opt} enable - disable or enable XMinorTick, enbale='on' by default Example 1: Without input arguments    my_XMinorTick Example 2: Without Color input argument    my_XMinorTick(5) Example 3: Set steps of XMinorTick and color XMinorTick

Generates normalized a-weigthing, -weighting, octave and one-third-octave digital filters. in matlab

The following Matlab project contains the source code and Matlab examples used for generates normalized a-weigthing, -weighting, octave and one-third-octave digital filters. . This series of M-files generates normalized A-weigthing, C-weighting, octave and one-third-octave digital filters.

Solves siso mean-square optimal control design problems: a(p)x = b(p)u + f(t) in matlab

The following Matlab project contains the source code and Matlab examples used for solves siso mean-square optimal control design problems: a(p)x = b(p)u + f(t) . Solves SISO mean-square optimal control design problems of the following form: Let the controlled plant is described by differential equation                  A(p)x = B(p)u + f(t), where x - scalar controlled variable, u - scalar control, A(p),B(p) are polynomials of p = d/dt, f(t) - external disturbance with known spectral density Sf=S(s)S(-s)=N(s)N(-s)/(T(s)T(-s)) (N(s),T(s) are Hurwitz polynomials).

Display unevenly distributed data in 2-d and 3-d as ordinary colour-coded, regularly spaced data. in matlab

The following Matlab project contains the source code and Matlab examples used for display unevenly distributed data in 2-d and 3-d as ordinary colour-coded, regularly spaced data. . FFGRID and DENSITY display unevenly distributed data in 2-D and 3-D as ordinary colour-coded, regularly spaced data.

Longlat2os in matlab

The following Matlab project contains the source code and Matlab examples used for longlat2os. os2longlat converts a UK Ordnance Survey grid reference to a longitude and latitude in radians   longlat2os converts a longitude and latitude to a U.

A succesful implementation of numerical computation of multivariate normal probabilities. in matlab

The following Matlab project contains the source code and Matlab examples used for a succesful implementation of numerical computation of multivariate normal probabilities. . A collection of M-Files that provide a succesful implementation of the difficult problem of numerical computation of multivariate normal probabilities.

The cport minitoolbox supplies basic functions to open, configure, read from,etc to ports. in matlab

The following Matlab project contains the source code and Matlab examples used for the cport minitoolbox supplies basic functions to open, configure, read from,etc to ports. . The CPORT minitoolbox supplies basic functions to open, configure, read from and write to serial and parallel ports under microsoft Windows 95/98 and (maybe) NT.

Contains a number of m-files for training and evaluation of the random neural network in matlab

The following Matlab project contains the source code and Matlab examples used for contains a number of m-files for training and evaluation of the random neural network . The RNNSIM v.2 package contains a number of m-files for training and evaluation of the random neural network. It is a more robust version of RNNSIM ver. 1.0 package without a graphical user interface.

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