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Hannah
Hannah
Last activity on 8 Feb 2024

Flipbook Mini Hack

I have been procrastinating on schoolwork by looking at all the amazing designs created in the last MATLAB Flipbook Mini Hack! They are just amazing. The voting is over but what are y'all's personal favorites? Mine is the flapping butterfly, it is for sure a creation I plan to share with others in the future!
I recently discovered a 2-minute video that introduces MatGPT, and I believe it's a resource worth sharing. The creator highlights MatGPT's impressive capabilities by demonstrating how it tackles the classic Travelling Salesman Problem.
With more than 13,000 downloads on File Exchange, MatGPT is gaining traction among users. I strongly recommend taking it for a spin to experience its potential firsthand.
how accurate are the answers of the AI Playground regarding information that are not specifiyed in the documentation?
Mike Croucher
Mike Croucher
Last activity on 29 Jan 2024

Pong Wars in MATLAB

One of my colleauges, Michio, recently posted an implementation of Pong Wars in MATLAB
Making me wonder about variations. What might the resulting patterns look with differing numbers of balls? Different physics etc?
We're thrilled to announce the roll-out of some new features that are going to supercharge your Playground experience! Here's what's new:
Copy/Download code from the script area
You can now effortlessly Copy/Download code from the script area with just a single click. Copy code or Download your script directly as .m files and keep your work organized and portable.We hope this will allow you to effortlessly transfer your work from Playground to MATLAB Desktop/Online.
Run Code directly from the Chat panel
Execute code snippets from the chat section with a single click. This new affordance means saving a step since you no longer have to insert code and then hit run from the toolstrip to execute instead just hit run in the chat panel to see the output immediately in the script area
Enhanced visual Experience
Customize your Playground workspace by expanding or collapsing the chat and script sections. Focus on what matters most to you, whether it's AI chat or working on your script.
We hope you will love these updates. Try them out and let us know your feedback.
Mike Croucher
Mike Croucher
Last activity on 22 Oct 2024

Multiple AIs in the chat playground

When I want to understand a problem, I'll often use different sources. I'll read different textbooks, blog posts, research papers and ask the same question to different people. The differences in the solutions are almost always illuminating.
I feel the same way about AIs. Sometimes, I don't want to ask *THE* AI...I want to ask a bunch of them. They'll have different strengths and weaknesses..different personalities if you want to think of it that way.
I've been playing with the AI chat arena and there really is a lot of difference between the answers returned by different models. https://lmarena.ai/?arena
I think it would be great if the MATLAB Chat playgroundwere to allow the user to change which AI they were talking with.
What does everyone else think?
I have been finding the AI Chat Playground very useful for daily MATLAB use. In particular it has been very useful for me in basically replacing or supplementing dives into MATLAB documentation. The documentation for MATLAB is in my experience uniformly excellent and thorough but it is sometimes lengthy and hard to parse and the AI Chat is a great one stop shop for many questions I have. However, I would find it very useful if the AI Chat could answer my queries and then also supply a link directly to the documentation. E.g. a box at the bottom of the answer that is basically
"Here is the documentation on the functions AI Chat referred to in this response"
could be neat.
I recently wrote about the new ODE solution framework in MATLAB over the The MATLAB Blog The new solution framework for Ordinary Differential Equations (ODEs) in MATLAB R2023b » The MATLAB Blog - MATLAB & Simulink (mathworks.com)
This was a very popular post at the time - many thousands of views. Clearly everyone cares about ODEs in MATLAB.
This made me wonder. If you could wave a magic wand, what ODE functionality would you have next and why?
Hi
I am using simulink for the frequency response analysis of the three phase induction motor stator winding.
The problem is that i can't optimise the pramaeter values manually, for this i have to use genetic algrothem. But iam stucked how to use genetic algorithum to optimise my circuit paramter values like RLC. Any guidence will be highly appreciated.
I am a beginner of deep learning, and meet with some problems in learning the MATLAB example "Denoise Signals with Adversarial Learning Denoiser Model", hope very much to get help!
Denoise Signals with Adversarial Learning Denoiser Model - MATLAB & Simulink - MathWorks China
1. visualizaition of the features
It is my understanding that the encoded representation of the autoencoder is the features of the original signal. However in this example, the output dimension of the encoder is 64xSignalLength. Does it mean that every sample point of the signal has 64 features?
2. usage of the residual blocks
The encoder-decoder model uses residual blocks (which contribute to reconstructing the denoised signal from the latent space, ). However, only the encoder output is connected to the discriminator. Doesn't it cause the prolem that most features will be learned by the residual blocks, and only a few features that could confuse the discriminator will be learned by the encoder and sent to the discriminator?
Matt J
Matt J
Last activity on 29 Jan 2024

3D polyshapes

Is there a reason for TMW not to invest in 3D polyshapes? Is the mathematical complexity of having all the same operations in 3D (union, intersection, subtract,...) prohibitive?
James Prestegard
James Prestegard
Last activity on 12 Jan 2024

Training a deep neural net

I have been developing a neural net to extract a set of generative parameters from an image of a 2-D NMR spectrum. I use a pair of convolution layers each followed by a fullyconnected layer; the pair are joined by an addtion layer and that fed to a regression layer. This trains fine, but answers are sub-optimal. I woudl like to add a fully connected layer between the addtion layer and regression, but training using default training scripts simply won't converge. Any suggestions? Maybe I can start with the pre-trained weights for the convolution layers, but I don't know how to do this.
JHP
Shore
Shore
Last activity on 30 Dec 2023

AI Chat: Thumbs Up/Down

This is not a question, it is my attempt at complying with the request for thumbs up/down voting. I vote thumbs up, for having AI.....
I am not sure if specific AI errors are to be reported. Other messages I just read from others here and the AI Chat itself clearly state that errors abound.
My AI request was: "Plot 300 points of field 2"
AI Chat gave me, in part:
data = thingSpeakRead(channelID, 'Fields', 2, 'NumPoints', 300, 'ReadKey', readAPIKey);
% Extract the field values
field1Values = data.Field1;
% Plot the data
plot(field1Values);
The AI code failed due to "Dot indexing is not supported for variables of this type"
So, I corrected the code thus to get the correct plot:
data = thingSpeakRead(channelID, 'Fields', 2, 'NumPoints', 300, 'ReadKey', readAPIKey);
% Extract the field values
%field1Values = data.Field1;
% Plot the data
plot(data);
I see great promise in AI Chat.
Opie
Quick answer: Add set(hS,'Color',[0 0.4470 0.7410]) to code line 329 (R2023b).
Explanation: Function corrplot uses functions plotmatrix and lsline. In lsline get(hh(k),'Color') is called in for cycle for each line and scatter object in axes. Inside the corrplot it is also called for all axes, which is slow. However, when you first set the color to any given value, internal optimization makes it much faster. I chose [0 0.4470 0.7410], because it is a default color for plotmatrix and corrplot and this setting doesn't change a behavior of corrplot.
Suggestion for a better solution: Add the line of code set(hS,'Color',[0 0.4470 0.7410]) to the function plotmatrix. This will make not only corrplot faster, but also any other possible combinations of plotmatrix and get functions called like this:
h = plotmatrix(A);
% set(h,'Color',[0 0.4470 0.7410])
for k = 1:length(h(:))
get(h(k),'Color');
end
We are thrilled to announce the grand prize winners of our MATLAB Flipbook contest! This year, we invited the MATLAB Graphics Infrastructure team, renowned for their expertise in exporting and animation workflows, to be our judges. After careful consideration, they have selected the top three winners:
1st place - Rolling fog / Tim
Judge comments: Creative and realistic rendering with well-written code
2nd place - Christmas Tree / Zhaoxu Liu
Judge comments: Festive and advanced animation that is appropriate to the current holiday season.
3rd place - Energy / Nikolay Velkov
Judge comments: Nice translation of existing shader logic to MATLAB that produces an advanced and appealing visual effect.
In addition, after validating the votes, we are pleased to announce the top 10 participants on the leaderboard:
Congratulations to all! Your creativity and skills have inspired many of us to explore and learn new skills, and make this contest a big success!
The MATLAB Flipbook Mini Hack contest has concluded! During the 4 weeks, over 600 creative animations have been created. We had a lot of fun and a great learning experience! Thank you, everyone!
Now it’s the time to announce week 4 winners. Note that grand prize winners will be announced shortly after we validate votes on winning entries.
Realism:
Tim / Moonrun
Daniel Pereira / Earth with labels!
O / Skywheel
Vasilis Bellos / Isle of Storms
Holiday & Season:
Zhaoxu Liu / slandarer / The Fierce Ghost of Halloween
Shanshan / Snowman
Jr / timeless 80s
Abstract:
VMM / Diffusion/Reaction
Adrien Leygue / a walk in 13D
Jan Studnicka / River
Nikolay Velkov / Energy
leon t / Stable Manifold of Lorenz System
Cartoon:
Sarah / rock hammer
Congratulations, weekly winners!We will reach out to you shortly for your prizes.
Looking for an opportunity to practice your AI skills on a real-world problem? Interested in AI for climage change? Sign up for the Kelp Wanted challenge, which tasks participants with developing an algorithm that can detect the presence of kelp forests from satellite images.
Participants of all skill levels from anywhere in the world are welcome to compete!
MathWorks provides the following resources for all participants:
Have you marveled at the breathtaking, natural-looking animations crafted by the creative minds in the Flipbook Mini Hack contest? Think of @Tim, @Jenny Bosten, and @Zhaoxu Liu / slandarer- their work is nothing short of extraordinary.
So, what's their secret? Adam Danz, a developer in the MATLAB Graphics and Charting team and a top community contributor, has graciously unveiled the mysteries in his latest blog post - "Creating natural textures with power-law noise: clouds, terrains, and more." The post offers simple, step-by-step instructions and code snippets, empowering you to grasp these enchanting techniques effortlessly.
Check it out and we hope it sparks your creativity and serves as a wellspring of inspiration. With only 3 days remaining before the contest draws to a close, it's time to dive into the code and let your imagination soar!