tag:www.mathworks.com,2005:/matlabcentral/fileexchange/feedMATLAB Central File Exchangeicon.pnglogo.pngMATLAB Central - File ExchangeUser-contributed code library2015-01-31T00:59:08-05:00229191100tag:www.mathworks.com,2005:FileInfo/494592015-01-31T05:34:52Z2015-01-31T05:34:52ZPower quality improvement using DPFC.Simulink model of IEEE 2010 paper.<p>The DPFC is derived from the Unified Power Flow Controller (UPFC). The DPFC can be considered as a UPFC with an eliminated common dc link. The active power ex-change between the shunt and series converters, which is through the common dc link in the UPFC, is now through the transmission lines at the third-harmonic frequency. The DPFC employs the distributed FACTS (D-FACTS) concept, which is to use multiple small-size single-phase converters instead of the one large-size three-phase series converter in the UPFC. The large number of series converters provides redundancy, thereby increasing the sys-tem reliability. As the D-FACTS converters are single-phase and floating with respect to the ground, there is no high-voltage isolation required between the phases. Accordingly, the cost of the DPFC system is lower than the UPFC. The DPFC has the same control capability as the UPFC, which comprises the adjustment of the line impedance, the transmission angle, and the bus voltage.
<br />This simulation (simulink model) is based on the IEEE paper :
<br />A FACTS Device: Distributed Power-Flow Controller (DPFC), IEEE TRANSACTIONS ON POWER ELECTRONICS, VOL. 25, NO. 10, OCTOBER 2010</p>
<p>Contact details:
<br /><a href="mailto:ankitceo@gmail.com">ankitceo@gmail.com</a></p>ankit kumarhttp://www.mathworks.com/matlabcentral/profile/authors/6122296-ankit-kumarMATLAB 7.9 (R2009b)SimPowerSystemsSimulinkMATLABNo requirements, can be simulated on any matlab/simulink version on or above R2009.falsetag:www.mathworks.com,2005:FileInfo/491572015-01-25T19:38:07Z2015-01-31T04:57:28Zinpolygon_for_gpuinpolygon function that works using gpuArray<p>This is a point-in-polygon function that can run on a gpu using large test point array sizes. It uses a simple ray-casting algorithm without pre-processing or "on" tolerance checks. Therefore it may not give the exact same results as inpolygon. Inputs must all be gpuArray objects in order to run on the gpu. The inputs take the form of MATLAB's inpolygon function. The parallel process occurs once for every vertex of the polygon, so large numbers of vertices will run slow. I had to have around around 1e5-1e7 test points to see speedup on my simple gaming GPU on a polygon with 1e4 vertices. I am hoping that re-implementing this using mex CUDA code will result in faster run-times. For best results, the number of test points should be close to the maximum array size on your GPU.
<br />This implementation of the ray-casting algorithm is based on C code by W. Randolf Franklin, which can be found at <a href="http://www.ecse.rpi.edu/Homepages/wrf/Research/Short_Notes/pnpoly.html">http://www.ecse.rpi.edu/Homepages/wrf/Research/Short_Notes/pnpoly.html</a></p>
<p>Any advice is welcome on how to speed up this algorithm, or make it more useful. Thanks!</p>
<p>Example:</p>
<p>L = linspace(0,2.*pi,6);
<br />xv = gpuArray(cos(L)');
<br />yv = gpuArray(sin(L)');</p>
<p>pts_x=gpuArray(rand(1e5,1));
<br />pts_y=gpuArray(rand(1e5,1));</p>
<p>tic
<br />in=inpolygon_for_gpu(pts_x, pts_y, xv, ,yv);
<br />toc</p>Sulimon Sattarihttp://www.mathworks.com/matlabcentral/profile/authors/4255258-sulimon-sattariMATLAB 8.0 (R2012b)Parallel Computing ToolboxGPU device that supports NVIDIA CUDA codefalsetag:www.mathworks.com,2005:FileInfo/494582015-01-31T01:24:47Z2015-01-31T01:24:47ZTransmission Line parameter calculator toolThis is a tool for calculation of transmission line parameters<p>This is the MATLAB code to a basic transmission line parameter calculator tool. It allows calculation of basic parameters like strip width, spacing etc. for a range of transmission lines</p>Lakshmi Nairhttp://www.mathworks.com/matlabcentral/profile/authors/6124473-lakshmi-nairMATLAB 7.10 (R2010a)falsetag:www.mathworks.com,2005:FileInfo/453522014-02-03T19:35:24Z2015-01-31T01:09:04ZMulti-Focus Image Fusion for Visual Sensor Networks in DCT DomainSimulation of two multi-focus image fusion methods in DCT domain: 1.DCT+Variance 2.DCT+Variance+CV<p>Attached is the simulation of following multifocus image fusion methods:
<br />
<br />(1) DCT+Variance
<br />(2) DCT+Variance+CV
<br />
<br />proposed in:
<br />
<br />M.B.A. Haghighat, A. Aghagolzadeh, H. Seyedarabi, "Multi-Focus Image Fusion for Visual Sensor Networks in DCT Domain," Computers and Electrical Engineering, vol. 37, no. 5, pp. 789-797, Sep. 2011.
<br /><a href="http://dx.doi.org/10.1016/j.compeleceng.2011.04.016">http://dx.doi.org/10.1016/j.compeleceng.2011.04.016</a>
<br />
<br />M.B.A. Haghighat, A. Aghagolzadeh, H. Seyedarabi, "Real-time fusion of multi-focus images for visual sensor networks," 6th Iranian Machine Vision and Image Processing (MVIP), pp. 1-6, IEEE, 2010.</p>Mohammad Haghighathttp://www.mathworks.com/matlabcentral/profile/authors/2857455-mohammad-haghighatMATLAB 8.2 (R2013b)Image Processing ToolboxMATLABfalsetag:www.mathworks.com,2005:FileInfo/467902014-05-29T14:58:28Z2015-01-31T01:08:34ZGabor WaveletsThis program generates a custom Gabor filter bank; and extracts the image features using them.<p>First function named "gaborFilterBank" generates a custom-sized Gabor filter bank. It creates a u*v array, whose elements are m by n matrices; each matrix being a 2-D Gabor filter.
<br />Second function named "gaborFeatures" extracts the Gabor features of the image.
<br />It creates a column vector, consisting of the image's Gabor features.
<br />At the end of each file there is a Show section that plots the filters and shows the filtered images. These are only for illustration purpose, and you can comment them as you wish.
<br />
<br />Details can be found in:
<br />
<br />M. Haghighat, S. Zonouz, M. Abdel-Mottaleb, "Identification Using Encrypted Biometrics," Computer Analysis of Images and Patterns, Springer Berlin Heidelberg, pp. 440-448, 2013.</p>Mohammad Haghighathttp://www.mathworks.com/matlabcentral/profile/authors/2857455-mohammad-haghighatMATLAB 8.2 (R2013b)Image Processing ToolboxSignal Processing ToolboxMATLABfalsetag:www.mathworks.com,2005:FileInfo/459262014-03-18T16:36:56Z2015-01-31T01:07:20ZFeature Mutual Information (FMI) Image Fusion MetricA non-reference image fusion metric based on mutual information of image features<p>FMI calculates the Feature Mutual Information (FMI), the non-reference performance metric for fusion algorithms, proposed in:
<br />
<br />M.B.A. Haghighat, A. Aghagolzadeh, H. Seyedarabi, "A Non-Reference Image Fusion Metric Based on Mutual Information of Image Features," Computers and Electrical Engineering, vol. 37, no. 5, pp. 744-756, Sept. 2011.
<br /><a href="http://dx.doi.org/10.1016/j.compeleceng.2011.07.012">http://dx.doi.org/10.1016/j.compeleceng.2011.07.012</a>
<br />
<br />
<br />This code is the implementation of FAST-FMI, presented in:
<br />
<br />M. Haghighat, M.A. Razian, “Fast-FMI: non-reference image fusion metric,” 8th International Conference on Application of Information and Communication Technologies (AICT), pp. 1-3, 2014.</p>Mohammad Haghighathttp://www.mathworks.com/matlabcentral/profile/authors/2857455-mohammad-haghighatMATLAB 8.4 (R2014b)Image Processing ToolboxWavelet ToolboxMATLAB40861falsetag:www.mathworks.com,2005:FileInfo/408612013-03-19T19:18:41Z2015-01-31T01:06:26ZMulti-Focus Image Fusion in DCT DomainSimulation of two multifocus image fusion methods: 1.DCT+Variance 2.DCT+Variance+CV<p>Attached is the simulation of following multi-focus image fusion methods:
<br />
<br />(1) DCT+Variance
<br />(2) DCT+Variance+CV
<br />
<br />proposed in:
<br />
<br />M.B.A. Haghighat, A. Aghagolzadeh, H. Seyedarabi, "Multi-Focus Image Fusion for Visual Sensor Networks in DCT Domain," Computers and Electrical Engineering, vol. 37, no. 5, pp. 789-797, Sep. 2011.
<br /><a href="http://dx.doi.org/10.1016/j.compeleceng.2011.04.016">http://dx.doi.org/10.1016/j.compeleceng.2011.04.016</a>
<br />
<br />M.B.A. Haghighat, A. Aghagolzadeh, H. Seyedarabi, "Real-time fusion of multi-focus images for visual sensor networks," 6th Iranian Machine Vision and Image Processing (MVIP), pp. 1-6, IEEE, 2010.</p>Mohammad Haghighathttp://www.mathworks.com/matlabcentral/profile/authors/2857455-mohammad-haghighatMATLAB 8.4 (R2014b)Image Processing ToolboxMATLAB45926falsetag:www.mathworks.com,2005:FileInfo/446302013-12-06T19:29:20Z2015-01-31T01:05:14ZGabor Feature ExtractionThis program generates a custom Gabor filter bank; and extracts the image features using them.<p>First function named "gaborFilterBank" generates a custom-sized Gabor filter bank. It creates a u*v array, whose elements are m by n matrices; each matrix being a 2-D Gabor filter.
<br />Second function named "gaborFeatures" extracts the Gabor features of the image.
<br />It creates a column vector, consisting of the image's Gabor features.
<br />At the end of each file there is a Show section that plots the filters and shows the filtered images. These are only for illustration purpose, and you can comment them as you wish.
<br />
<br />Details can be found in:
<br />
<br />M. Haghighat, S. Zonouz, M. Abdel-Mottaleb, "Identification Using Encrypted Biometrics," Computer Analysis of Images and Patterns, Springer Berlin Heidelberg, pp. 440-448, 2013.</p>Mohammad Haghighathttp://www.mathworks.com/matlabcentral/profile/authors/2857455-mohammad-haghighatMATLAB 8.4 (R2014b)Image Processing ToolboxSignal Processing ToolboxMATLABfalsetag:www.mathworks.com,2005:FileInfo/494572015-01-30T22:59:59Z2015-01-30T22:59:59ZLattice Reduction MIMOA matlab simulator for lattice reduction algorithms used for MIMO detection<p>The matlab code provided here is used for the following paper:
<br />S. Shahabuddin, J. Janhunen, A. Ghazi, Z. Khan, and M. Juntti, “A Customized Lattice Reduction Multiprocessor for MIMO Detection", in IEEE International Symposium on Circuits and Systems, May 2015, Lisbon, Portugal.
<br />The paper can be found at:
<br /><a href="http://arxiv.org/abs/1501.04860">http://arxiv.org/abs/1501.04860</a></p>Shahriar Shahabuddinhttp://www.mathworks.com/matlabcentral/profile/authors/2871129-shahriar-shahabuddinMATLAB 8.4 (R2014b)falsetag:www.mathworks.com,2005:FileInfo/491202015-01-22T20:39:03Z2015-01-30T21:25:30ZX-13 Toolbox for Seasonal FilteringMatlab toolbox providing access to X-13 seasonal adjustemnt programs of the US Census Bureau.<p>The X-13 Toolbox for Matlab is a shell for interacting with the programs of the US Census Bureau, known as X-13, that perform seasonal filtering. The X-13 programs are the "industry standard" and are widely used by many statistical agencies and researchers. The toolbox ought therefore to be useful for statisticians or economists who use Matlab, and who lacked access to the standard seasonal adjustment method until now.
<br />
<br />The toolbox contains a short documentation in a PDF. Maybe the easiest way to get started is to study the three demo files that are provided. The X-13 program has a plethora of specifications one can fiddle around with. The best source to learn this is the original US Census Bureau documentation. Their website also has working papers devoted to this topic (see <a href="https://www.census.gov/srd/www/x13as/">https://www.census.gov/srd/www/x13as/</a>).
<br />
<br />The original X-13 program can only be used with monthly or quarterly data. The X-13 toolbox therefore also provides a much simpler seasonal filter based on moving averages, but that works with timeseries of arbitrary frequency.
<br />
<br />Note: The toolbox requires freely available executables from the US Census Bureau in order to run. It attempts to download these executables automatically for you whenever you need one that is not on your harddrive. Of course, that works only if you are online, and it is limited to Windows computers. Versions of these programs for other operating systems are available from the Census website, however, and can easily be installed manually.
<br />
<br />Please comment below if you find this software useful.</p>Yvan Lengwilerhttp://www.mathworks.com/matlabcentral/profile/authors/1003439-yvan-lengwilerMATLAB 8.3 (R2014a)MATLABRequires software from the US Census Bureau. The toolbox will attempt to download this software automatically whenever needed. Tested only on a Windows computer.false