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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 would tell myself to understand vectorization. MATLAB is designed for operating on whole arrays and matrices at once. This is often more efficient than using loops.
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
I noticed a couple new replies show up on the recent poll a day or so ago, but since then, the page can't be loaded anymore in any browser I've tried.
Is MathWorks going to spend 5 years starting in 2024 making Python the #1 supported language?
I'm not sure it's authentic information, and am looking forward to a high level of integration with python.
Reference:
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
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
Judge comments: Festive and advanced animation that is appropriate to the current holiday season.
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:
Holiday & Season:
Abstract:
Cartoon:
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!
Kali
Kali
Last activity 2023-12-21

Write a matlab script that will print the odd numbers, 1 through 20, in reverse.
I cannot figure out how to do this correctly, please help.
In Week 3, we reached the 400-animations milestone! Let’s work together to achieve the 500-animations goal!
During the last week of the contest, we strongly encourage you to inspire your colleagues, classmates, or friends to vote. Voters will also have the opportunity to win a MATLAB T-shirt.
Mini Hack Winners - Week 3
Math, Physics, or Science explanation:
Most creative remix:
40:
Math is beautiful:
Mashup (Combined themes):
Jr / balloons IV (40 & multi-entry story)
Nature:
Holidays:
Congratulations, winners!
In week 4, we’d love to see more entries in the following categories:
  • Holidays:
  • Seasons:
  • Abstract:
  • Mashup (mixed categories)
A gentle reminder that you have a direct impact on the next generation of animation tools in MATLAB! Don’t forget to share your thoughts and ideas with us.
i've finished writing the code for my ~masterpiece~ and it doesn't run on the contest new entry page. it runs on matlab on my desktop and in the matlab live editor in my browser, but not where i really need it to. usually it'll draw the first frame the first time i run the code in a new window, but not any subsequent times. whether i hit "run" or "create animation", the screen grays out as it's supposed to, but then returns to normal without generating the first frame or animation.
i'm not getting a timeout warning or any error messages. i timed the code on my laptop and it takes about 100ish seconds to run and generate the animation the first time i run it before clearing everything from my workspace (and then it takes about twice as long each subsequent time, which makes me a bit nervous. can't figure out why this is the case at all!), which is well within the 255 second limit for the contest. as far as i know, the most computationally expensive function i'm using is patch(). i'm pretty close to the character limit, but i don't know if that's part of the problem.
i tried vectorizing some of the code instead of using for loops, which made the code run slightly slower. i tried using a nested function instead of using drawframe() and an auxiliary function, but that didn't help. i tried clearing all variables except f at the end of drawframe() to no avail. i tried using the close command at the start of drawframe(), with similar success. i updated chrome, closed a bunch of windows, tried safari, used my sister's laptop, all with no luck.
has anyone else had this or a similar problem? any advice?
thanks!
Just in two weeks, we already have 300 entries and 2,000 votes! We are so impressed by your creative styles, artistic talents, and ingenious programming techniques.
Now, it’s time to announce the weekly winners!
Mini Hack Winners - Week 2
Time & Space:
Trees:
Cartoon:
Symbolism:
Realism:
Fractal:
Multi-Entry Stories:
Explanatory:
Light:
MATtropolis:
Congratulations! Each of you won your choice of a T-shirt, a hat, or a coffee mug. We will contact you after the contest ends.
New categories for Week 3!
  • 40: MathWorks will celebrate its 40th Anniversary in 2024. You will have opportunities to win special prizes!
  • Most creative remix
Categories we’d love to see more entries in
Finally, just a reminder that you have a direct impact on the next generation of animation tools in MATLAB! Don’t forget to share your thoughts and ideas with us.
Hello, all!
This is my first post after just joining this discussion, so please forgive me and provide kind assistance if I have posted to the wrong subsection!
I have a good interest in learning sql server course and right now I am taking help from various platforms like https://www.coursera.org/ https://www.udemy.com/
Also I have a doubt that is it a good option to learn from platforms like this or I should go for some sql server online training . I have searched for the solution of my queries in various above platforms which helped me up to some extent only as it was not directly given by any expert or trainer.
Hoping in getting a quick response
Thankyou in advance.
Adrian Segura
Adrian Segura
Last activity 2023-11-28

Hello, I am a student and I am working on a neural network for a line follower car and I would like you to recommend a tutorial to implement it in simulink.
Dear contest participants,
Happy Friday! I am thrilled to share some exciting news with you. Cleve Moler, the father of MATLAB, has just published a captivating blog post dedicated to our outstanding Flipbook Mini Hack contest!
In his blog post, Cleve expresses his genuine admiration for the multitude of creative styles, artistic talents, and ingenious programming techniques that have been showcased throughout the contest. What's even more remarkable is that he handpicked some of his personal favorites! You don't want to miss this opportunity to see what Cleve has to say.
But that's not all! Your exceptional animations have sparked immense interest among the MathWorks teams. This means you have a direct impact on the next generation of animation tools in MATLAB! We value your thoughts and ideas, so please don't hesitate to share them with us.
Let's keep up the phenomenal work in the remaining two weeks, and together, we'll continue to push the boundaries of creativity and innovation.
Wishing you all an incredible weekend ahead!
Enthusiastically yours,
Chen