tag:www.mathworks.com,2005:/matlabcentral/fileexchange/feedMATLAB Central File Exchangeicon.pnglogo.pngMATLAB Central - File ExchangeUser-contributed code library2014-11-24T02:18:25-05:00224141100tag:www.mathworks.com,2005:FileInfo/484902014-11-18T01:40:21Z2014-11-24T07:01:04ZLynx MATLAB ToolboxA toolbox for the design of complex machine learning experiments<p>Lynx is a research-oriented MATLAB toolbox for designing in a fast way supervised machine learning experiments. Details of a simulation can be specified under a configuration file, and the toolbox takes charge of loading data, partitioning it, testing the algorithms and visualizing the results. Additionally, it has support for parallelizing the experiments, and enabling GPU support. This makes large experiments easily repeatable and modifiable.
<br />We have currently pre-implemented several algorithms (e.g. support vector machines, kernel ridge regression...), optimization routines (grid-search procedures, searching the optimal feature subset...), and datasets.
<br />You can see examples of use (taken from my research papers) on:
<br /><a href="http://ispac.ing.uniroma1.it/scardapane/software/code/">http://ispac.ing.uniroma1.it/scardapane/software/code/</a>
<br />Please do not hesitate to contact me for any help. The toolbox has been tested on MATLAB R2013a.</p>Simonehttp://www.mathworks.com/matlabcentral/fileexchange/authors/427352MATLAB 8.1 (R2013a)MATLAB Distributed Computing ServerMATLAB Report GeneratorNeural Network ToolboxParallel Computing ToolboxStatistics ToolboxMATLAB3162784214773215282191224093273842806731272falsetag:www.mathworks.com,2005:FileInfo/484292014-11-12T03:57:19Z2014-11-24T04:14:07ZLyapunov Nonlinear Control GUIThis GUI can simulate and regulate a nonlinear dynamic system.<p>Type 'launch' to run the GUI. Many examples are included.
<br />This GUI can be used to regulate any controllable, nonlinear system to a user-specified setpoint.* It uses a switched Lyapunov control function. The nonlinear system can be of any order and with any number of inputs. There is an adaptation option as well but it hasn't been throughly tested yet.</p>
<p>For now, only simulations are possible. In the future, this app will be integrated with ROS (the Robot Operating System) so it can be used to control hardware, as well.</p>
<p>*The proof is pending peer review.</p>Andy Zelenakhttp://www.mathworks.com/matlabcentral/fileexchange/authors/523364MATLAB 7.12 (R2011a)MATLABfalsetag:www.mathworks.com,2005:FileInfo/482302014-10-23T00:13:03Z2014-11-24T02:59:38ZWindTraderWindTrader 程序化交易终端是基于Wind资讯®发布的MATLAB数据及交易接口,用于量化投资活动中账户和策略的建立及管理、模拟和真实交易的监视及控制的程序化交易终端应用。<p>1. WindTrader解决什么问题?
<br />Wind用户在使用Wind资讯®发布的MATLAB数据及交易接口编写策略实施模拟或者真实交易时缺少一个可以实时刷新账户信息和委托单信息以及便捷地管理策略的用户图形界面.
<br />2. WindTrader如何工作?
<br />WindTrader以MATLAB App的形式发布和安装,并完全以GUI的形式工作.</p>Stevenhttp://www.mathworks.com/matlabcentral/fileexchange/authors/514325MATLAB 8.0 (R2012b)MATLAB需要事先安装Wind资讯®发布的MATLAB数据及交易接口falsetag:www.mathworks.com,2005:FileInfo/485472014-11-24T01:16:32Z2014-11-24T01:17:31ZHand Geometry Recognition Biometric System Matlab CodeHand Geometry Recognition Biometric<p>Hand Geometry Recognition System V3 : Simple and Effective Source Code for Hand Geometry Recognition System.see More : <a href="http://matlab-recognition-code.com/hand-geometry-recognition-system-matlab-full-source-code/">http://matlab-recognition-code.com/hand-geometry-recognition-system-matlab-full-source-code/</a>
<br />We Have Developed a Fast And Optimized Algorithm For Hand Geometry Recognition Based on Neural Networks. Proposed Approach Does not Require any Particular Hardware Since Extracted Features Are Computed Without Assuming Any Fixed Hand Positioning and Also a Low-cost Webcam Can Be Used for Image Acquisition.</p>Hamdi Boukamchahttp://www.mathworks.com/matlabcentral/fileexchange/authors/516650MATLAB 7.14 (R2012a)falsetag:www.mathworks.com,2005:FileInfo/484052014-11-10T05:18:55Z2014-11-24T00:32:28ZLight Field Toolbox v0.3A set of tools for working with light field (aka plenoptic) imagery in Matlab<p>This is a set of tools for working with light field (aka plenoptic) imagery in Matlab. Features include decoding, camera calibration, rectification, colour correction and visualization of light field images. New in version 0.3 are functions for reading gantry-style light fields and for directly reading Lytro LFP files including support for Lytro Illum and Lytro Desktop 4.
<br />Download the sample light field pack at <a href="http://www-personal.acfr.usyd.edu.au/ddan1654/LFToolbox0.3_Samples1.zip">http://www-personal.acfr.usyd.edu.au/ddan1654/LFToolbox0.3_Samples1.zip</a> . Sample calibration datasets can be found at <a href="http://marine.acfr.usyd.edu.au/plenoptic-imaging">http://marine.acfr.usyd.edu.au/plenoptic-imaging</a> .</p>Donald Dansereauhttp://www.mathworks.com/matlabcentral/fileexchange/authors/522379MATLAB 8.2 (R2013b)Image Processing ToolboxOptimization ToolboxDSP System ToolboxComputer Vision System ToolboxMATLAB8919falsetag:www.mathworks.com,2005:FileInfo/479502014-09-29T12:45:43Z2014-11-24T00:24:30Zmseb(x,y,errBar,lineProps,transparent)Creates a 2D plot containing multiple lines with pretty shaded error bars.<p>Multiple Shaded Error Bars (MSEB) makes a 2-d plot containing multiple lines with pretty shaded error bars.
<br />This is an extension of the popular shadedErrorBar, by Rob Campbell, enabling plotting of multiple data lines with overlapping errorbars, as well as turning off legends for all elements but the main lines. MSEB is directed at using the default renderer instead of openGL, which is known to cause problems, e.g., with logarithmic axes and not being able to save figures as vector graphics in the eps-format. To avoid the error bar patches concealing previously plotted main lines, the different elements are plotted in a suitable order. The default setting plot edges of overshadowed patches in an non-obtrusive manner so all error bars can be seen but avoids cluttering of the plot (see the third example on how to customise this). The patches are plotted in reverse order to make sure the first entry is "on top".
<br />Inputs:
<br />x - vector of x values [optional, can be left empty]
<br />y - vector of y values or a matrix of C x N, where C is the number of
<br /> lines to be plotted and N is the number of samples in each line and
<br /> should be equal to length(X)
<br />errBar - if a vector we draw symmetric errorbars. If it has a
<br /> size of [C,length(x),2] then asymmetric error bars are drawn,
<br /> with row 1 being the upper bar and row 2 being the lower
<br /> bar. In the present version errBar does not support two function
<br /> handles.
<br />lineProps - [optional. Can also be set as "[]" for default settings].
<br /> Struct containing fields that define lineproperties for the
<br /> plot function. It is possible to only define some of the
<br /> fields.
<br /> .col - cell array defining the color of each line, e.g., 'b' for
<br /> blue.
<br /> .style - linestyle of the lines from y-data. Default is '-'.
<br /> .width - linewidth of the lines from y-data. Default is 2.
<br />.edgestyle - linestyle of edges that are overlapped by errorbars from
<br /> other lines.
<br />transparent - [optional, 0 by default] if ==1 the shaded error
<br /> bar is made transparent, which forces the renderer
<br /> to be openGl. However, if this is saved as .eps the
<br /> resulting file will contain a raster not a vector
<br /> image. openGL does not support having logarithmic axes.
<br />Outputs
<br />H - structure with an element for each line entry containing handles to
<br /> the generated plot objects (e.g. H(c) contains the handles to the
<br /> c'th line entry.</p>Andreas Trier Poulsenhttp://www.mathworks.com/matlabcentral/fileexchange/authors/507719MATLAB 8.3 (R2014a)MATLAB26311falsetag:www.mathworks.com,2005:FileInfo/485462014-11-23T23:32:52Z2014-11-23T23:32:52Zpeterson-tim-j/Groundwater-Statistics-ToolboxA highly flexible toolbox for getting more quantitiative value from groundwater monitoring data.<p>The Groundwater Statistics Toolbox (GST) is a highly flexible statistical toolbox for getting more quantitiative value from groundwater monitoring data. Currently, the toolbox contains a highly flexible groundwater hydrograph time-series modeling framework that facilitates the following:
<br /> Decomposition of hydrographs into individual drivers, such as climate and pumping
<br /> Decomposition of hydrographs into time-periods causing observed trends
<br /> Interpolation or extrapolation of the observed hydrograph.</p>
<p>To begin building time-series model, please first read the model documentation. It can be accessed by opening MatLab and changing the current path (within MatLab) to the location of 'GroundwaterStatistics Toolbox.m'. Once there, enter the following command within the MatLab command window (ignore the quotation marks): "doc GroundwaterStatisticsToolbox". The documentation that should appear contains details of the model and commands to access an example model.</p>
<p>Details of the time-series framework are avaiable at:</p>
<p>Peterson T. J and Western A. W., (2014), Nonlinear Groundwater time-series modeling of unconfined groundwater head, Water Resources Research, DOI: 10.1002/2013WR014800</p>Tim Petersonhttp://www.mathworks.com/matlabcentral/fileexchange/authors/496484MATLAB 7.10 (R2010a)1893720355falsetag:www.mathworks.com,2005:FileInfo/485452014-11-23T23:26:46Z2014-11-23T23:26:46Zpeterson-tim-j/Catchment_Resilience_ModelCatchment hydrological resilence model as detailed in Peterson, Western and Argent (2014)<p>This project presents a catchment hydrological resilence model for modelling hydrological attractors within a semi-distributed catchment. The model is written in object-oriented Matlab and allows the identification of hydrological attractors using limit-cycle continuation and stochastic simulations. A versions of this model was published with Peterson and Western (2014) and using in Peterson et al. (2009) Peterson et al. (2014). Please contact Tim Peterson (<a href="mailto:timjp@unimelb.edu.au">timjp@unimelb.edu.au</a>) for copies of the papers.</p>Tim Petersonhttp://www.mathworks.com/matlabcentral/fileexchange/authors/496484MATLAB 7.10 (R2010a)MATLAB23821falsetag:www.mathworks.com,2005:FileInfo/333812011-10-19T23:19:21Z2014-11-23T18:14:04ZJSONlab: a toolbox to encode/decode JSON files in MATLAB/OctaveJSONlab is an open-source JSON/UBJSON encoder and decoder (parser) for MATLAB and Octave.<p>** JSONLAB v1.0 RC2 (Optimus RC2) is released on 11/23/2014.**
<br />JSONlab is a component of iso2mesh toolbox (<a href="http://iso2mesh.sf.net">http://iso2mesh.sf.net</a>). For the latest information regarding JSONlab, please visit its homepage at <a href="http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab">http://iso2mesh.sf.net/cgi-bin/index.cgi?jsonlab</a>
<br />JSONlab is a free and open-source implementation of a JSON/UBJSON encoder and decoder in the native MATLAB language. It can be used to convert a MATLAB data structure (array, struct, cell, struct array and cell array) into JSON/UBJSON formatted strings, or to decode a JSON/UBJSON file into MATLAB data structure. JSONlab supports both MATLAB and GNU Octave (a free MATLAB clone).</p>
<p>JSON (JavaScript Object Notation) is a highly portable, human-readable and "fat-free" text format to represent complex and hierarchical data. It is as powerful as XML, but less verbose. JSON format is widely used for data-exchange in applications, and is essential for the wild success of Ajax and Web2.0.</p>
<p>UBJSON (Universal Binary JSON) is a binary JSON format, specifically optimized for compact file size and better performance while keeping the semantics as simple as the text-based JSON format. Using the UBJSON format allows to wrap complex binary data in a flexible and extensible structure, making it possible to process complex and large dataset without accuracy loss due to text conversions.</p>
<p>We envision that both JSON and its binary version will serve as part of the mainstream data-exchange formats for scientific research in the future. It will provide the flexibility and generality achieved by other popular general-purpose file specifications, such as HDF5, with significantly reduced complexity and enhanced performance.</p>
<p>JSONlab provides two functions, loadjson.m -- a MATLAB->JSON decoder,
<br />and savejson.m -- a MATLAB->JSON encoder, for the text-based JSON, and
<br />two equivallent functions -- loadubjson and saveubjson for the binary
<br />JSON. The savejson, loadubjson and saveubjson functions were written by
<br />Qianqian Fang, while the loadjson.m script was derived from the previous works by the following people:</p>
<p>- Nedialko Krouchev: <a href="http://www.mathworks.com/matlabcentral/fileexchange/25713">http://www.mathworks.com/matlabcentral/fileexchange/25713</a>
<br /> date: 2009/11/02
<br />- FranÃ§ois Glineur: <a href="http://www.mathworks.com/matlabcentral/fileexchange/23393">http://www.mathworks.com/matlabcentral/fileexchange/23393</a>
<br /> date: 2009/03/22
<br />- Joel Feenstra: <a href="http://www.mathworks.com/matlabcentral/fileexchange/20565">http://www.mathworks.com/matlabcentral/fileexchange/20565</a>
<br /> date: 2008/07/03</p>
<p>Please find detailed online help at <a href="http://iso2mesh.sourceforge.net/cgi-bin/index.cgi?jsonlab/Doc">http://iso2mesh.sourceforge.net/cgi-bin/index.cgi?jsonlab/Doc</a></p>Qianqian Fanghttp://www.mathworks.com/matlabcentral/fileexchange/authors/33904MATLAB 7.4 (R2007a)MATLABCommunications System ToolboxSimulink Verification and ValidationJSONlab is platform independent.falsetag:www.mathworks.com,2005:FileInfo/483322014-11-02T22:33:56Z2014-11-23T17:09:10ZAutomated phenotyping of mouse behaviorAutomated analysis of common behavior tasks used by the neuroscience community<p>This work includes automated routines for the analysis of several commonly used behavior tasks used by the neuroscience community. We automated the scoring of: Barnes Maze, Social interaction, spatial object recognition, fear conditioning, zero maze, y-maze, open field, and morris water maze.
<br />Please visit <a href="http://www.seas.upenn.edu/~molneuro/autotyping.html">www.seas.upenn.edu/~molneuro/autotyping.html</a> for more information.</p>Tapanhttp://www.mathworks.com/matlabcentral/fileexchange/authors/508699MATLAB 8.1 (R2013a)Please download "mmread" from the matlab file exchange and put the extracted folder within the parent autotyping folder.false