tag:www.mathworks.com,2005:/matlabcentral/fileexchange/feedMATLAB Central File Exchangeicon.pnglogo.pngMATLAB Central - File ExchangeUser-contributed code library2018-01-18T10:16:24-05:00320541100tag:www.mathworks.com,2005:FileInfo/657592018-01-18T14:54:36Z2018-01-18T15:10:54ZNumeric Heisler chartIt solves numerically the heat exchange problems requiring the Heisler temperature charts.<p>In heating/cooling problems the Heisler dimensionless temperature charts are used. But sometimes they are very difficult to be used. Why not try to solve numerically the problem?
<br />The proposed function "get_dt_terms" allows solving numerically the one-dimensional transient conduction solutions inside plates, infinite circular cylinders and spheres, calculating the temperature at their centre point. The extension to any other internal point of the geometry is very simple.</p>Giuseppe Altierihttp://www.mathworks.com/matlabcentral/profile/authors/202013-giuseppe-altieriMATLAB 9.0 (R2016a)Octave compatible.falsetag:www.mathworks.com,2005:FileInfo/657602018-01-18T15:06:58Z2018-01-18T15:06:58ZArduino Temperature Control Lab for Simulink and MATLABMATLAB and Simulink programs to control heaters (2), read temperatures (2), and control LED<p>This plug-and-play lab reinforces transient modeling, parameter estimation, and feedback control to maintain temperature. There are two heaters and two temperature sensors. The heater power output is adjusted to maintain a desired temperature setpoint. Thermal energy from the heater is transferred by conduction, convection, and radiation to the temperature sensor. Heat is also transferred away from the device to the surroundings. This lab is a resource for model identification and controller development. It is a pocket-sized lab with the purpose of reinforcing control theory for students. Many universities around the world have adopted this lab for process control education. The lab is also used for the online courses Process Dynamics and Control (<a href="https://apmonitor.com/pdc">https://apmonitor.com/pdc</a>) and Dynamic Optimization (<a href="https://apmonitor.com/do">https://apmonitor.com/do</a>).
<br />This lab teaches principles of system dynamics and control. In particular, this lab reinforces:
<br />Dynamic modeling with balance equations
<br />The difference between manual and automatic control
<br />Step tests to generate dynamic data
<br />Fitting dynamic data to a First Order Plus Dead Time (FOPDT) model
<br />Obtaining parameters for PID control from standard tuning rules
<br />Tuning the PID controller to improve performance Process Control Temperature Lab
<br />Instructions are available for building the kit at <a href="http://apmonitor.com/che436/uploads/Main/Hands_on_Process_Control_CACHE.pdf">http://apmonitor.com/che436/uploads/Main/Hands_on_Process_Control_CACHE.pdf</a> or for purchase from <a href="https://apmonitor.com/heat.htm">https://apmonitor.com/heat.htm</a></p>John Hedengrenhttp://www.mathworks.com/matlabcentral/profile/authors/2999773-john-hedengrenMATLAB 9.0 (R2016a)Arduino support package as an Add-onfalsetag:www.mathworks.com,2005:FileInfo/657582018-01-18T13:24:57Z2018-01-18T13:24:57Z5046850468<p>50468</p>Pratap Patilhttp://www.mathworks.com/matlabcentral/profile/authors/11956976-pratap-patilMATLAB 9.3 (R2017b)falsetag:www.mathworks.com,2005:FileInfo/236112009-04-09T09:43:32Z2018-01-18T13:24:17Zpeakfit.mCommand-line peak fitter for time-series signals. Version 9.0, January 2018<p>peakfit(signal,center,window,NumPeaks,peakshape,extra,NumTrials,start,autozero,fixedparameters,plots,bipolar,minwidth,DELTA,clipheight)
<br />A command-line peak fitting program for time-series signals, written as a self-contained Matlab function in a single m-file. Uses a non-linear optimization algorithm to decompose a complex, overlapping-peak signal into its component parts. The objective is to determine whether your signal can be represented as the sum of fundamental underlying peaks shapes. Accepts signals of any length, including those with non-integer and non-uniform x-values. Fits any number of peaks of 44 different shapes, including models with multiple shapes. This is a command line version, usable from a remote terminal. It is capable of making multiple trial fits with sightly different starting values and taking the one with the lowest mean fit error, and it can estimate the standard deviation of peak parameters from a single signal using the bootstrap method.</p>Tom O'Haverhttp://www.mathworks.com/matlabcentral/profile/authors/870532-tom-o-haverMATLAB 9.3 (R2017b)falsetag:www.mathworks.com,2005:FileInfo/657572018-01-18T12:20:32Z2018-01-18T13:15:04Zsurf_slices(varargin)Plot 3D data as series of slices in specified axis<p>Rather than plotting a 3D volume, instead plot a series of slices.
<br />Like surf() except without interpolation in one of the axes.
<br />surf_slices(Z): slices of matrix Z where size(Z)=[m,n]
<br />surf_slices(x,y,Z): slices of matrix Z, where length(x)=n and length(y)=m
<br />surf_slices(x,y,Z,'axis',axis): Change slicing axis (either 1 or 2)
<br />The plot is constructed by overlaying a surf plot with a series of lines plotted along the ridges of the slices.
<br />To reveal the mesh structure of the plot, use:
<br />ax = gca;
<br />ax.Children(end) = 'k';
<br />Note that because a slice has a finite width (the width is the separation of the axis points), you may cut off the end of the data if you set the axis limits manually.</p>Talfan Evanshttp://www.mathworks.com/matlabcentral/profile/authors/4987800-talfan-evansMATLAB 9.1 (R2016b)falsetag:www.mathworks.com,2005:FileInfo/655482017-12-29T11:21:58Z2018-01-18T12:13:47ZUpward continuation of Grid dataUpward continuation of grid data of potential methods of Exploration Geophysics.<p>Upward continuation is a process of determining the data on a surface above a surface on which the data is recorded or known. It utilizes the Green's identities. Here the Fourier domain utilization has been used to calculate the upward continuation of the Gravity and Magnetic data of Exploration Geophysics. The code returns the contour map of observed data as well the upward continued data, level being decided by the user input.</p>Bibhu Dashttp://www.mathworks.com/matlabcentral/profile/authors/8361910-bibhu-dasMATLAB 8.3 (R2014a)falsetag:www.mathworks.com,2005:FileInfo/657422018-01-16T06:52:56Z2018-01-18T08:08:51ZMCDM toolsnine MCDM ranking methods<p>MCDM tools contains a set of MatLab functions implementing for rank methods for task Multi-Criteria Decision Making (MCDM) methods:
<br />SAW, MOORA, COPRAS, VIKOR, MABAC, TOPSIS, DIDEAL, ORESTE1,2, PROMETHEE II
<br />+ Gui for MCDM tools.pdf
<br />+ MCDM_Res.xlsx - result file</p>Irik Mukhametzyanovhttp://www.mathworks.com/matlabcentral/profile/authors/9911903-irik-mukhametzyanovMATLAB 7.9 (R2009b)falsetag:www.mathworks.com,2005:FileInfo/470232014-06-21T11:40:25Z2018-01-18T06:04:58ZChebfun - current versionNumerical computation with functions<p>Chebfun is an open-source software system for numerical computing with functions. The mathematical basis is piecewise polynomial interpolation implemented with what we call “Chebyshev technology”. The foundations are described, with Chebfun examples, in the book Approximation Theory and Approximation Practice (L. N. Trefethen, SIAM 2013). Chebfun has extensive capabilities for dealing with linear and nonlinear differential and integral operators, and also includes continuous analogues of linear algebra notions like QR and singular value decomposition. The Chebfun2 extension works with functions of two variables defined on a rectangle in the x-y plane.
<br />Most Chebfun commands are overloads of familiar MATLAB commands — for example sum(f) computes an integral, roots(f) finds zeros, and u = L\f solves a differential equation.
<br />To get a sense of the breadth and power of Chebfun, a good place to start is by looking at our Examples (<a href="http://www.chebfun.org/examples/">http://www.chebfun.org/examples/</a>) or the introductory Guide (<a href="http://www.chebfun.org/docs/guide/">http://www.chebfun.org/docs/guide/</a>).
<br />Please contact us with any questions/comments at <a href="mailto:help@chebfun.org">help@chebfun.org</a>.</p>Chebfun Teamhttp://www.mathworks.com/matlabcentral/profile/authors/1823057-chebfun-teamMATLAB 8.2 (R2013b)MATLABfalsetag:www.mathworks.com,2005:FileInfo/433922013-09-06T19:26:47Z2018-01-18T06:04:47ZDavidMercier/NIMSA Matlab GUI to plot and to analyze (nano)indentation data (obtained with conical indenters)<p>A Matlab toolbox to plot and to analyze nanoindentation data (with conical indenters) </p>David MERCIERhttp://www.mathworks.com/matlabcentral/profile/authors/4027816-david-mercierMATLAB 8.5 (R2015a)MATLABYAML Matlab
(https://code.google.com/p/yamlmatlab/)falsetag:www.mathworks.com,2005:FileInfo/602372016-11-15T17:17:47Z2018-01-18T06:04:26Zcengique/pandora-matlabPlotting and Analysis of Neuroscience Database-Oriented Research Applications<p>PANDORA is a Matlab Toolbox for analyzing neuronal electrophysiology data and constructing databases. The project is currently in transition to a new version. See the Github Wiki for branch information (<a href="https://github.com/cengique/pandora-matlab/wiki">https://github.com/cengique/pandora-matlab/wiki</a>).</p>Cengiz Gunayhttp://www.mathworks.com/matlabcentral/profile/authors/200271-cengiz-gunayMATLAB 7.3 (R2006b)false