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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.
  1. 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.
  2. Animations blog post. The post demonstrates some coding techniques that can make your animations easier.
  3. 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.
  4. 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.
  5. 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.
Check out our 100th animation by Tim. Isn't it amazing?
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 :)
The MATLAB AI Chat Playground is open to everyone!
Check it out here on the community: https://www.mathworks.com/matlabcentral/playground
MATLAB AI Chat Playground Screenshot
I just published a blog post announcing the release.
The 2023 community contest - MATLAB Flipbook Mini Hack - starts today on Nov. 6th!
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:
  1. Before you start, we highly recommend you check out the two examples - Bouncing and Spinning - to understand how the contest works.
  2. 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!
You are invited to join our 2023 community contest – MATLAB Flipbook Mini Hack! This year’s contest revolves around creating interesting animations using MATLAB.
Whether you are a seasoned MATLAB user or just getting started, this contest offers a fantastic opportunity to showcase your skills, learn from others, and engage with the vibrant MATLAB Central community.
Timeframe
This contest runs for 4 weeks from Nov. 6th to Dec. 3rd.
How to play
  • Create a new animation or remix an existing one with up to 2,000 characters of code.
  • Simply vote on the animations you love!
Prizes
You will have opportunities to win compelling prizes, including Amazon gift cards, MathWorks T-shirts, and virtual badges. We will give out both weekly prizes and grand prizes.
Check out the gallery and vote on the animations you like.
The MATLAB Central Community team
Adam Danz
Adam Danz
Last activity 2023 年 12 月 9 日

I rarely/never save .fig files
47%
Continue working on it later
16%
Archive for future reference
23%
Share within my organization
10%
Share outside my organization
2%
Other (please leave a comment)
2%
2097 票
Julian
Julian
Last activity 2024 年 2 月 5 日

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.
Matt J
Matt J
Last activity 2024 年 3 月 1 日

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
In the past year, we've witnessed an exponential growth of ChatGPT and other Generative AI tools. AI has quickly become a transformative force across industries, from tech giants to small startups, and even community sites like ours. For instance, Stack Overflow announced its plan to leverage AI tools to draft a question or tag content; Quora built a ChatGPT bot to answer questions; and GitHub is piloting the AI tool for personalized content.
This trend in the community landscape makes me wonder what MATLAB Central community, especially in MATLAB Answers, can do to integrate AI and enhance the community.
Share with us your ideas in the comment session. Ideally one comment per idea, so that others can vote on a secific idea or have deeper discussions about it.
Adam and Heather will be discussing new features in R2023b and answering your questions in a few hours - visit the link below to check out the preview and sign up for notification.
We launched the Discussions area with 6 channels, based on the existing types of content we see today in the MATLAB Central community.
I'm curious which channels you are most interested in participating, or which channels are missing.
Tell us your thoughts here!
Adam Danz just launched a new blog about MATLAB Graphics and App Building.
As you know, He has been a prolific contributor to MATLAB Answers and one of his answers recently won the Editor's Choice Award.
If there are any topics or questions you are interested in, please share with Adam, and I am sure he will get those into his blog.
4 months ago, the new API was published to access content on the MATLAB Central community. I shared my MATLAB code to access the API at that time, but the team just released the official SDK.
Houman and Rameez will talk about how you can model wireless networks (5G, WLAN, Bluetooth, 802.11ax WLAN mesh, etc.) in MATLAB in the upcoming livestream. They will start with the basics such as nodes, links, topology and metrics. Then they will introduce a new free add-on library that lets you model such networks, and show you how to use it.
Bookmark this link:
Congratulations, @Adam Danz for winning the Editor's Pick badge awarded for MATLAB Answers, in recognition of your awesome solution in overlapping images in grid layout.
Thank you for going to great lengths to help a user in this thread by suggesting alternative approach to representing stack of playing cards in MATLAB, highlighting very interesting features like hggroup.
This badge recognizes awesome answers people contribute and yours was picked for providing a very detailed and helpful answer.
Thank you so much for setting a high standard for MATLAB Answers and for your ongoing contribution to the community.
MATLAB Central Team
Congratuations, @Voss, for htting this important miletone!
You had a meteoric rise to in our community since you started answering questions in June 2020.
You provided 3218 answers and 926 votes. You are ranked #23 in the community. Thank you for your contribution to the community and please keep up the good track record!
MATLAB Central Team
MATLAB Onramp is a free online tutorial and it has been very popular with new MATLAB users to learn how to use it, and MathWorks have been adding more and more modules. The lastest one just dropped https://matlabacademy.mathworks.com/details/power-systems-simulation-onramp/orps
It shows you the basics of power system simulation by modeling a simple microgrid. You will learn how to simulate and measure three-phase circuits, and how to evaluate algorithms like droop control and maximum power point tracking.
Thats the task:
Given a square cell array:
x = {'01', '56'; '234', '789'};
return a single character array:
y = '0123456789'
I wrote a code that passes Test 1 and 2 and one that passes Test 3 but I'm searching a condition so that the code for Test 3 runs when the cell array only contains letters and the one for Test 1 and 2 in every other case. Can somebody help me?
This is my code:
y = []
[a,b]=size(x)
%%TEST 3
delimiter=zeros(1,a)
delimiter(end)=1
delimiter=repmat(delimiter,1,b)
delimiter(end)=''
delimiter=string(delimiter)
y=[]
for i=1:a*b
y = string([y x(i)])
end
y=join(y,delimiter)
y=erase(y,'0')
y=regexprep(y,'1',' ')
%%TEST 1+2
for i=1:a*b
y = string([y x(i)])
y=join(y)
end
y=erase(y,' ' )