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Struct is an easy way to combine different types of variants. But now MATLAB supports classes well, and I think class is always a better alternative than struct. I can't find a single scenario that struct is necessary. There are many shortcomings using structs in a project, e.g. uncontrollable field names, unexamined values, etc. What's your opinion?
I am confused, is the matlab answer better or Julia’s?
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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.
Have you ever used Live Tasks in MATLAB? MathWorks development team would like to get some feedback on your experience – what did you like and not like. Especially, if you know about it but don’t use it frequently, we would like to understand why?
Please tell us what you think by submitting your response to this form https://forms.office.com/r/ui1EGqAFDx
how accurate are the answers of the AI Playground regarding information that are not specifiyed in the documentation?
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.
MathWorks just released three new courses on Coursera liseted below. If you work with image or video data and are wanting to incorporate deep learning techniques into your workflow, this is a great opporutnity. The course creators monitor the discussion forums, so you can ask questions and get feedback on your work. Below are links to the three courses and a quick description of a project you'll complete in each.
- Introduction to Computer Vision for Deep Learning. You'll train a classifier to classify images of people signing the American Sign Language alphabet.
- Deep Learning for Object Detection. Move from just classification to finding object locations. You'll train a model to find different types of parking available on the MathWorks campus.
- Advanced Deep Learning Techniques for Computer Vision. You'll train anomaly detection models for medical images and use AI-assisted labeling auto label images.
Can anyone provide insight into the intended difference between Discussions and Answers and what should be posted where?
Just scrolling through Discussions, I saw postst that seem more suitable Answers?
What exactly does Discussions bring to the table that wasn't already brought by Answers?
Maybe this question is more suitable for a Discussion ....
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?
how can i use this AI?
We are excited to unveil the ‘Open in MATLAB Online from File Exchange’ feature, which offers MATLAB users a new way to open File Exchange content!
Previously, to experiment with File Exchange code, you were required to download the file and execute it in MATLAB. But now, there's a quicker and easier way to explore the code!
You will find the ‘Open in MATLAB Online’ button next to the ‘Download’ button (see the screenshot below). A simple click transports you directly into the MATLAB Online workflow. It's that straightforward and effortless.
We strongly encourage you to try this new feature. Please share your questions, comments, or ideas by responding to this post!
Hello Community!
We are working on a new translation experience for the MathWorks website and products. The goal is to make it easy for people to see content in the best language for them.
Step 1 is learning from those of you who use another language instead of, or in addition to English. If this sounds like you, we'd love your response to a brief survey.
Feel free to comment here as well. Thanks in advance!
We've released an open-source implementation of STIPA (Speech Transmission Index for Public Address) on GitHub!
What is STIPA?
Speech Transmission Index is a metric designed to assess the quality of speech transmission through a communication channel. It quantifies the intelligibility of speech signals based on amplitude modulations, providing a standardized measure crucial for evaluating public address systems and communication equipment. STIPA is a version of STI using a simplified measurement method and only one test signal.
Quality Representation:
STI values range from 0 to 1, categorizing speech transmission quality from bad to excellent. The raw STI score can be transformed into the likelihood of intelligibility of syllables, words, and sentences being comprehended.
Verification Tests:
To ensure reliability, we've conducted verification tests according to the IEC 60286-16 standard. Download the test signals and run the stipaVerificationTests.m script from our GitHub repository.
Control Measurements:
We've performed comparative measurements in a university auditorium, showcasing the validity of our implementation.
License:
Our STIPA implementation is distributed under the GNU General Public License 3, reflecting our commitment to open-source collaboration.
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.
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 just thinking to make a project on software defined ratio SDR using matlab and its toolboxes but I am UG student in ECE don't know how to start can we have discussion here and want the guidance from the best or good persons in the field of wireless communication
Hello, Community Members!
Every day, we witness the incredible exchange of knowledge as over 100,000 users visit our community for answers or to get some code. We have such a vibrant community because of the dedicated group of contributors who volunteer their time and expertise to help one another.
We learned that many community users are looking for different ways to show their appreciation to contributors. In response, we're thrilled to announce the launch of our latest feature – Skill Endorsements.
When you visit a contributor's profile page, you'll notice a brand-new 'Endorsements' tab. Here, you have the power to acknowledge the skills of your fellow members by either endorsing a new skill or bolstering existing ones.
But it's more than just saying "thank you." By highlighting the strengths of our members, you're contributing to an environment of trust and making it easier for users to connect with experts in specific areas.
So, take a moment to reflect: Who has made a difference in your community experience? Whose expertise has guided you through a challenge? Show your appreciation and support their contributions – start endorsing skills today!
Your participation makes all the difference.
Warm regards,
MATLAB Central Community Team
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!
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?
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
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