MATLAB Central - Detecting key press with pause. What are newsgroups? The newsgroups are a worldwide forum that is open to everyone. Newsgroups are used to discuss a huge range of topics, make announcements, and trade files. Discussions are threaded, or grouped in a way that allows you to read a posted message and all of its replies in chronological order. This makes it easy to follow the thread of the conversation, and to see what’s already been said before you post your own reply or make a new posting. Newsgroup content is distributed by servers hosted by various organizations on the Internet. Messages are exchanged and managed using open- standard protocols. No single entity “owns” the newsgroups. On Feb 10, 12:44 pm, 'NIcholas ' <dsfa.@aol.com> wrote: > I want to run a loop like this > for i=1:100 >. do something. > pause; > end > > How do I detect the key the person pressed that broke the pause? In the example. Function message = pass_or_fail(StudentData) Exam_avg = mean(StudentData.Exam); if(Exam_avg >= 70) message = 'You pass!'; else message = 'You fail!'; end return; 7.2. Input assertion routines Good programming style dictates. Clc clear M=100; Re=5000; L=0.444; dx=L/M; x(1)=0; for i=1:M; x(i+1)=x(i)+dx; delta(i)=5*x(i+1)/((Re)^0.5) end plot(x(1:M),delta) %axis equal grid on title('Relationship between Boundary Layer Thicknes and Reynolds Number. There are thousands of newsgroups, each addressing a single topic or area of interest. The MATLAB Central Newsreader posts and displays messages in the comp. How do I read or post to the newsgroups? MATLAB Central. You can use the integrated newsreader at the MATLAB Central website to read and post messages in this newsgroup. MATLAB Central is hosted by Math. Works. Messages posted through the MATLAB Central Newsreader are seen by everyone using the newsgroups, regardless of how they access the newsgroups. There are several advantages to using MATLAB Central. One Account. Your MATLAB Central account is tied to your Math. Clc clear E=69e12; D=0.005; A=0.25*(pi)*(D)^2; I=(pi/4)*(D)^4; L=1; P=-100000; PP=(P/(12*E*I)); PPP=3/4 M=100; DX=L/M; for i=1:M/2; X(i)=i*DX; Y(i)=PP*X(i)*(PPP*(L^2)-(X(i))^2) end ii=M/2 for i=M/2:M-2; ii=ii-1 X(i)=i*DX; Y(i. This example shows how to detect and count cars in a video sequence using foreground detector based on Gaussian mixture models (GMMs). Works Account for easy access. Use the Email Address of Your Choice. Let's start from the end. Here is the final output of this chapter. When we play this video, we'll see the white cars are tagged with red marks. Your browser does not support the video tag. Canny edge detector algorithm matlab codes. This part gives the algorithm of Canny edge detector. The outputs are six subfigures shown in the same figure: Subfigure 1: The initial 'lena' Subfigure 2: Edge detection along X. Setting Up the C Compiler..2-6 Setting Up File Infrastructure and Paths.. 2-7 Compile Path Search Order..2-7 Can I Add Files to the Embedded MATLAB Path?. 2-7 When to Use. MATLAB Function Reference : Index. Symbols!-% & <1> <2> && ' <1> <2> * +. /: < = == > \ ^ | <1> <2> || ~ <1> <2> ~= Numerics 1-norm <1> <2>. Open source tools, information and interactive games related to laser optics, numerical modeling and detecting gravitational waves. The MATLAB Central Newsreader allows you to define an alternative email address as your posting address, avoiding clutter in your primary mailbox and reducing spam. Spam Control. Most newsgroup spam is filtered out by the MATLAB Central Newsreader. Tagging. Messages can be tagged with a relevant label by any signed- in user. Tags can be used as keywords to find particular files of interest, or as a way to categorize your bookmarked postings. 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The outputs are. six subfigures shown in the same figure: Subfigure 1: The initial "lena". Subfigure 2: Edge detection along X- axis direction. Subfigure 3: Edge detection along Y- axis direction. Subfigure 4: The Norm of the image gradient. Subfigure 5: The Norm of the gradient after thresholding. Subfigure 6: The edges detected by thinning. The matlab codes. The main. m file %%%%%%%%%%%%%%%. The algorithm parameters. Parameters of edge detecting filters. X- axis direction filter. Nx. 1=1. 0; Sigmax. Nx. 2=1. 0; Sigmax. Theta. 1=pi/2. % Y- axis direction filter. Ny. 1=1. 0; Sigmay. Ny. 2=1. 0; Sigmay. Theta. 2=0. % 2. The thresholding parameter alfa. Get the initial image lena. Image: lena. gif'). X- axis direction edge detection. Nx. 1,Sigmax. 1,Nx. Sigmax. 2,Theta. 1). Ix= conv. 2(w,filterx,'same'). Y- axis direction edge detection. Ny. 1,Sigmay. 1,Ny. Sigmay. 2,Theta. 2). Iy=conv. 2(w,filtery,'same'). Norm of the gradient (Combining the X and Y directional derivatives). NVI=sqrt(Ix.*Ix+Iy.*Iy). Norm of Gradient'). I_max=max(max(NVI)). I_min=min(min(NVI)). I_max- I_min)+I_min. Ibw=max(NVI,level.*ones(size(NVI))). After Thresholding'). Thinning (Using interpolation to find the pixels where the norms of. Ibw). if Ibw(i,j) > level. X=[- 1,0,+1; -1,0,+1; -1,0,+1]. Y=[- 1,- 1,- 1; 0,0,0; +1,+1,+1]. Z=[Ibw(i- 1,j- 1),Ibw(i- 1,j),Ibw(i- 1,j+1). Ibw(i,j- 1),Ibw(i,j),Ibw(i,j+1). Ibw(i+1,j- 1),Ibw(i+1,j),Ibw(i+1,j+1)]. XI=[Ix(i,j)/NVI(i,j), - Ix(i,j)/NVI(i,j)]. YI=[Iy(i,j)/NVI(i,j), - Iy(i,j)/NVI(i,j)]. ZI=interp. 2(X,Y,Z,XI,YI). Ibw(i,j) > = ZI(1) & Ibw(i,j) > = ZI(2). I_temp(i,j)=I_max. I_temp(i,j)=I_min. I_temp(i,j)=I_min. I_temp). title('After Thinning'). End of the main. m file %%%%%%%%%%%%%%%. The functions used in the main. Function "d. 2dgauss. This function returns a 2. D edge detector (first order derivative. D Gaussian function) with size n. Function "gauss. m". Function "dgauss. Back End of document.
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