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I think it would be a really great feature to be able to add an Alpha property to the basic "Line" class in MATLAB plots. I know that I have previously had to resort to using Patch to be able to plot semitransparent lines, but there are also so many other functions that rely on the "Line" class.
For example, if you want to make a scatter plot from a table with things specified into groups, you can use ScatterHistogram or gscatter but since gscatter uses the Line class, you can't adjust the marker transparency. So if you don't want the histograms, you are stuck with manually separating it and using scatter with hold on.
I saw this post on Answers.
I was impressed at the capability of the AI, as I have been at other times when I posed a question to it, at least some of the time. So much so that I wondered...
What if the AI were automatically applied to EVERY question on Answers? Would that be a good or bad thing? For example, suppose the AI automatically offers an answer to every question as soon as it gets posted? Of course, users would still be allowed to post their own, possibly better answers. But would it tend to disincentivise individuals from ansering questions?
Perhaps as bad, would it push Answers into the mode of a homework solving forum? Since if every homework question gets a possibly pretty good automatic AI generated solution, then every student will just post all HW questions, and the forum would quickly become overwhelmed.
I suppose one idea could be to set up the AI to post an answer to all un-answered questions that are at least one month old. Then students would not gain by posting their homework.
Hi Guys
Posting this based on a thought I had, so I don't really ahve any code however I would like to know if the thought process is correct and/or relatively accurate.
Consider a simple spring mass system which only allows compression on the spring however when there is tension the mass should move without the effect of the spring distrupting it, thus the mass is just thrown vertically upwards.
The idea which I came up with for such a system is to have two sets of dfferential equations, one which represents the spring system and another which presents a mass in motion without the effects of the spring.
Please refer to the below basic outline of the code which I am proposing. I believe that this may produce relatively decent results. The code essentially checks if there is tension in the system if there is it then takes the last values from the spring mass differential equation and uses it as initial conditions for the differential equation with the mass moving wothout the effects of the spring, this process works in reverse also. The error which would exist is that the initial conditions applied to the system would include effects of the spring. Would there be a better way to code such behaviour?
function xp = statespace(t,x,f,c,k,m)
if (k*x(1)) positive #implying tension
**Use last time step as initial conditions**
**differential equation of a mass moving""
end
if x(1) negative #implying that the mass in now moving down therefore compression in spring
**Use last time step as initial conditions**
**differential equation for a spring mass system**
end
end
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.
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.
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
Here's a MATLAB class I wrote that leverages the MATLAB Central Interface for MATLAB toolbox, which in turn uses the publicy available Community API. Using this class, I've created a few Favorites that show me what's going on in MATLAB Central - without having to leave MATLAB 🙂
The class has a few convenient queries:
  • Results for the last 7 days
  • Results for the last 30 days
  • Results for the current month
  • Results for today
And supporting a bunch of different content scopes:
  • All MATLAB Central
  • MATLAB Answers
  • Blogs
  • Cody
  • Contests
  • File Exchange
  • Exclude Answers content
The results are displayed in the command window (which worked best for me) and link to each post. Here's what that looks like for this command
>> CommunityFeed.thisMonth("app designer", CommunityFeed.Scope.ExcludeAnswers)
Let me know if you find this class useful and feel free to suggest changes.
New Cheat Sheet Alert!
Level up your data organization and access skills in MATLAB with our latest cheat sheet! Download the full cheat sheet on MATLAB GitHub for Students here.
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 voti
Julian
Julian
Last activity il 5 Feb 2024

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 il 1 Mar 2024

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.
Calling all students! New to MATLAB or need helpful resources? Check out our MATLAB GitHub for Students repository! Find MATLAB examples, videos, cheat sheets, and more!
Visit the repository here: MATLAB GitHub for Students
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: