tag:www.mathworks.com,2005:/matlabcentral/fileexchange/feedMATLAB Central File Exchangeicon.pnglogo.pngMATLAB Central - File ExchangeUser-contributed code library2015-03-02T20:21:16-05:00232011100tag:www.mathworks.com,2005:FileInfo/498632015-02-28T22:58:10Z2015-03-02T23:47:54ZDecentralized Path Planning For Coverage Using Gradient DescentPath planning algorithm using gradient-descent on way-points to cover interesting regions<p>"Decentralized Path Planning For Coverage using Gradient Descent Adaptive Control" is a recent IJRR (International Journal of Robotics Research) paper submitted by Soltero et. al from MIT (doi: 10.1177/0278364913497241). The algorithm presented in this paper is simulated. An interesting closed path controller has been implemented in the algorithm. This is done using the Voronoi cost function and the optimization is done using gradient descent method. In a map there are a few interesting regions which give sensory input to the robot. This algorithm helps the path of the robot to adapt according to the map provided and maximize the time spent on the interesting areas. Here the path changes for each iteration and tends to converge to the interesting region. The initial path of the robot is important since the map is not known to the robot and the initial path should preferably cover all the regions on the map so that we can obtain all the interesting regions on the map. You can change the interesting region and play with it. HAVE FUN!!!
<br />-coded by Srikanth.K.V.S and Aaron.T.Becker</p>Srikanth Kandanuru Venkata Sudarshanhttp://www.mathworks.com/matlabcentral/profile/authors/5900325-srikanth-kandanuru-venkata-sudarshanMATLAB 8.4 (R2014b)falsetag:www.mathworks.com,2005:FileInfo/498982015-03-02T22:20:29Z2015-03-02T22:20:29ZImage color filteringThis function provides a color filtering of a given image.<p>This function modifies a given image in order to keep a specific hue (given too) and to desaturate the rest of the image. This procedure originates a image with black and white colormap, excluding the parts colored with that hue. Input and output parameters are specificated in the function header.
<br />Example of use extracting the blue hue (H: 150º - 270º):
<br />I = imread('myimage.jpg');
<br />I = im2double(I);
<br />I_m = colorfilter(I_2,[150 270]);
<br />imshow(I_m,[]);</p>Víctor Martínezhttp://www.mathworks.com/matlabcentral/profile/authors/5962292-victor-martinezMATLAB 8.3 (R2014a)MATLABfalsetag:www.mathworks.com,2005:FileInfo/498972015-03-02T21:29:30Z2015-03-02T21:29:30ZSignature ToolThe Signature Tool extracts the interface of a Simulink subsystem.<p>The notion of subsystem is used in Simulink to represent systems inside systems in order to provide for hierarchical modeling. A Simulink subsystem has inports (explicit links to the subsystem), and outports (explicit links from the subsystem). We view inports and outports as the explicit interface of the subsystem. However, there are hidden (implicit) data dependencies in the Simulink’s subsystem. Hidden dependencies originate in two Simulink data mechanisms: data stores and Goto/From blocks.
<br />We present the Signature Tool, the tool that extracts the signature of a Simulink subsystem. A signature represents the interface of a Simulink subsystem, making the data flow into and out of the subsystem explicit. The tool identifies two useful signatures for a subsystem: strong signature and weak signature. The strong signature identifies the data mechanisms that are accessed by the subsystem or any of its children. The weak signature identifies the data mechanisms that a subsystem can access (those which are declared higher up in the hierarchy), but is not necessarily using. The Signature Tool can be used to either explicitly include the signatures in the model itself, or export the signatures into a text file.</p>
<p>For installation instructions, and instructions on how to use the tool, see README.txt.</p>
<p>For more about the theoretical background on signatures and how they can be used, an interested reader is referred to:</p>
<p>Marc Bender, Karen Laurin, Mark Lawford, Jeff Ong, Steven Postma, Vera Pantelic, "Signature Required - Making Simulink Dataflow and Interfaces Explicit," Proceedings of 2nd International Conference on Model-Driven Engineering and Software Development (MODELSWARD 2014), SCITEPRESS, 2014, 119-131. (Nominated for Best Paper Award)</p>
<p>For more about the capabilities of the tool and how it can be used in a model-based development with Simulink, see:</p>
<p>Vera Pantelic, Steven Postma, Mark Lawford, Alexandre Korobkine, Bennett Mackenzie, Jeff Ong, Marc Bender, "A Toolset for Simulink: Improving Software Engineering Practices in Development with Simulink," Proceedings of 3rd International Conference on Model-Driven Engineering and Software Development (MODELSWARD 2015), SCITEPRESS, 2014. (Won Best Paper Award)</p>Mark Lawfordhttp://www.mathworks.com/matlabcentral/profile/authors/6052287-mark-lawfordMATLAB 7.13 (R2011b)SimulinkMATLABfalsetag:www.mathworks.com,2005:FileInfo/498962015-03-02T19:33:30Z2015-03-02T19:33:30ZModulationA basic GUI for understanding how Amplitude and Frequency Modulation is done.<p>This is a very basic modulation example for a few certain signal types. The main goal is to understand how modulation is done and how it is demodulated.</p>Berat Atmacahttp://www.mathworks.com/matlabcentral/profile/authors/6087953-berat-atmacaMATLAB 8.3 (R2014a)Signal Processing ToolboxMATLABfalsetag:www.mathworks.com,2005:FileInfo/460702014-03-28T15:12:11Z2015-03-02T18:33:32Zplot_subroutinesplots the subroutines in a function, and their dependencies on each other<p>plot_subfun('foo.m') plots a node map of the subroutines in a function, and their dependencies.
<br />The screenshot is a sample output for the function plot_subfun.m itself.</p>Christopher Pedersenhttp://www.mathworks.com/matlabcentral/profile/authors/2130826-christopher-pedersenMATLAB 8.4 (R2014b)MATLAB1592427608falsetag:www.mathworks.com,2005:FileInfo/498942015-03-02T18:03:35Z2015-03-02T18:03:35ZDCmotor_resolver couplingDC motor and resolver are coupled by connecting proper sensors check the performance<p>characteristics in Combined operation</p>H SAI MANIKANTA Ehttp://www.mathworks.com/matlabcentral/profile/authors/6178816-h-sai-manikanta-eMATLAB 5.2 (R10)SimscapeSimulinkfalsetag:www.mathworks.com,2005:FileInfo/498922015-03-02T17:00:53Z2015-03-02T17:00:53Z2D Poisson Solver using Zero Neumann boundary conditions - Theory Guide2D Poisson Solver using Zero Neumann boundary conditions - Theory Guide<p>2D Poisson Solver using Zero Neumann boundary conditions - Theory Guide</p>Koorosh Gobalhttp://www.mathworks.com/matlabcentral/profile/authors/6053464-koorosh-gobalMATLAB 8.3 (R2014a)Theoretical guide for 'poisson2Dneumann.m'falsetag:www.mathworks.com,2005:FileInfo/498912015-03-02T16:50:28Z2015-03-02T16:50:28ZRead all images in a directoryReads all the images in a given directory<p>A simple class that iterates through a given directory and loads all the images. You can either iterate through the images with the getNext() function or load all the images into a cell array with the getAll() function.</p>Philhttp://www.mathworks.com/matlabcentral/profile/authors/1921854-philMATLAB 8.4 (R2014b)MATLABNone, it should work on any Matlab version that supports classesfalsetag:www.mathworks.com,2005:FileInfo/498902015-03-02T16:43:26Z2015-03-02T16:43:26Zpoisson2Dneumann(F,L)Solves the 2D Poisson equation using zero neumann boundary condition<p>POISSON2DNEUMANN solves the the 2D poisson equation d2UdX2 + d2UdY2 = F, with the zero neumann boundary condition on all the side walls. We are using the discrete cosine transform to solve the Poisson equation with zero neumann boundary conditions.</p>Koorosh Gobalhttp://www.mathworks.com/matlabcentral/profile/authors/6053464-koorosh-gobalMATLAB 8.3 (R2014a)falsetag:www.mathworks.com,2005:FileInfo/498892015-03-02T15:38:42Z2015-03-02T15:38:42ZDSP Companion, Student Version, 3.0DSP Companion is instructional software designed to accompany a textbook.<p>The DSP Companion is instructional software designed to accompany the textbook “Digital Signal Processing using MATLAB”, Third Edition, by R. Schilling and S. Harris, published by Cengage Learning, Stamford CT. The DSP Companion is designed to be used both inside the classroom by the instructor and outside the classroom by the student. The student version includes GUI modules that allow students to interactively explore and compare design techniques covered in each chapter. They feature a common user interface that is simple to use and easy to learn. Also included are menu options for viewing examples, figures, tables, definitions, propositions, algorithms, and solutions to selected problems that appear throughout the text.</p>Robert Schillinghttp://www.mathworks.com/matlabcentral/profile/authors/51179-robert-schillingMATLAB 8.4 (R2014b)MATLABWindows XP or later, Adobe Readerfalse