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We reached the 100 animations milestone in less than 3 days! We are thrilled to see so many creative entries and talented members learning from each other.
Note that this contest is not just for experts. People with all skill levels can participate, improve their MATLAB skills, and have fun!
We have created new resources and tips for you to get started.
- Contest introductory video. The 3-minute video provides you with a quick introduction to how the contest works and how to create a simple animation.
- Animations blog post. The post demonstrates some coding techniques that can make your animations easier.
- AI Chat Playground. This is a new community app we just released. You can leverage the Generative AI tool to write initial draft MATLAB code or modify existing one.
- Get ideas from previous Mini Hack contests. There is a large gallery of amazing images, which provide you with ideas and code to start with.
- Remix is highly encouraged. Learning from others is the most effective way to learn. Make some SMALL changes and see what it would look like.
We look forward to seeing more of you joining us and having more fun!
Seeing a colleague make this mistake (one I've had to fix multiple times in other's work too) makes me want to ask the community: would you like the awgn() function/blocks to give the option for creating a SNR at the bandwidth of the signal? Your typical flow is something like this:
- Create a signal, usually at some nominal upsampling factor (e.g., 4) such that it's now nicely over sampled, especially if you're using a RRC or similar pulse shaping filter.
- Potentially add a frequency offset (which might make the sample frequency even higher)
- Add AWGN channel model for a desired SNR
- Put this into your detector/receiver model
The problem is, when someone says, "I'm detecting XYZ at foo SNR," it should not magically improve as a function of the oversample. The problem isn't that awgn() generates white noise, that's what it's supposed to do and the typical receiver has noise across the entire band. The problem is that SNR is most properly defined as the signal power over the noise power spectral density times the signal's noise equivalent bandwidth. Now I looked and there's no handy function for computing NEBW for an input signal (there's just a function for assessing analysis windows). In practice it can get a bit tricky. The occupied bandwidth or HPBW are often close enough to the NEBW, we're usually not haggling over hundredths of a dB. So, in my not so humble opinion, the "measured" flag for awgn() should give an option for bandwidth matching or at least document the behavior better in the help page. All too often I'm seeing 3-6 (or worse) dB errors because people aren't taking the signal's bandwidth into account.
Unlike last year's contest, there are some new technologies this year that might offer some advantages. Namely generative AI's like ChatGPT, Bard, etc. Not to be excluded, MathWorks just launched the AI Chat Playground :)
good afternoon everyone my name is Dundu lawan haruna ,i'm a final year student at the department of computer engineering ABU Zaria, Nigerian , and i wanted to do my final year project based on computer vision : project topic , designing an eye glasses to help those people with visual imparement to be able to navigate enviroment efficiently , that's why i need a support from you guys ,all advised are highly well come , thank you for your support.
Participants across all skill levels are welcome to join! You can participate by creating a new animation or remixing an existing one with up to 2,000 characters of MATLAB code.
Contest Tips:
- Before you start, we highly recommend you check out the two examples - Bouncing and Spinning - to understand how the contest works.
- Share your thoughts, ask questions, or connect with others in our contest discussion channel.
Note that the first week (Nov. 6th, 2023, ~ Nov. 12th, 2023) is for creating entries only. Voting does not begin until the second week.
We look forward to seeing your creative work. Let the contest begin!
Share your fun photos in the comments!
I know the latest version of MATLAB R2023b has this feature already, put it should be added to R2023a as well because of its simplicity and convenience.
Basically, I want to make a bar graph that lets me name each column in a basic bar graph:
y=[100 99 100 200 200 300 500 800 1000];
x=["0-4" "5-17" "18-29" "30-39" "40-49" "50-64" "65-74" "75-84" "85+"];
bar(x,y)
However, in R2023a, this isn't a feature. I think it should be added because it helps to present data and ideas more clearly and professionally, which is the purpose of a graph to begin with.
Recently, I came across a post about the JIT compiler on this Korean blog. In the post. The writer discussed the concept of the "Compile Threshold" and how it is calculated.
"The JVM accumulates the number of calls for each method called and compiles when the number exceeds a certain number. In other words, there is a standard for checking how often it is called and then deciding, 'It is time to compile.' This standard is called the compilation threshold. But what is this and why should it be used as a standard?"
The concept of the "Compile Threshold," as used above, seems to be more commonly associated with Tracing just-in-time compilation.
The writer used the simple Java code below to calculate the threshold.
for (int i = 0; i < 500; ++i) {
long startTime = System.nanoTime();
for (int j = 0; j < 1000; ++j) {
new Object();
}
long endTime = System.nanoTime();
System.out.printf("%d\t%d\n", i, endTime - startTime);
}
Since the MATLAB execution engine uses JIT compilation, I just wanted to perform the same experiment that the writer did.
I experimented using simple codes based on the code in the blog. I iterated a function 500 time using for-loop and calculated the execution time for each iteration using tic and toc. Then I plotted the execution time for each loop as blow. First five execution times are much higher than followings (10 times!) The test is very rough so I am not sure that I can conclude "MATLAB has Compile Threshold and it is 5!" but this value is actually correct ;-)
t0 = 0;
tfinal = 10;
y0 = [20;20];
timeToRun = zeros(500,1);
for i = 1:500
tStart = tic;
[preypeaks,predatorpeaks] = solvelotka(t0, tfinal, y0);
tEnd = toc(tStart);
timeToRun(i) = tEnd;
end
VS Code Extension for MATLAB was introduced back in April and has been downloaded 75K times since. Do people here use VS Code for writing MATLAB code?
Would it be a good thing to have implicit expansion enabled for cat(), horzcat(), vertcat()? There are often situations where I would like to be able to do things like this:
x=[10;20;30;40];
y=[11;12;13;14];
z=cat(3, 0,1,2);
C=[x,y,z]
with the result,
C(:,:,1) =
10 11 0
20 12 0
30 13 0
40 14 0
C(:,:,2) =
10 11 1
20 12 1
30 13 1
40 14 1
C(:,:,3) =
10 11 2
20 12 2
30 13 2
40 14 2
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