I am excited to announce that I am currently working on a book project centered around Matrix Algebra, specifically designed for MATLAB users. This book aims to cater to undergraduate students in engineering, where Matrix Algebra serves as a foundational element.
Matrix Algebra is not only pivotal in understanding complex engineering concepts but also in applying these principles effectively in various technological solutions. MATLAB, renowned for its powerful computational capabilities, is an excellent tool to explore and implement these concepts, making it a perfect companion for this book.
As I embark on this journey to create a resource that bridges theoretical matrix algebra with practical MATLAB applications, I am looking for one or two knowledgeable individuals who have a firm grasp of both subjects. If you have experience in teaching or applying matrix algebra in engineering contexts and are familiar with MATLAB, your contribution could be invaluable.
Collaborators will help in shaping the content to ensure it is educational, engaging, and technically robust, making complex concepts accessible and applicable for students.
If you are interested in contributing to this project or know someone who might be, please reach out to discuss how we can work together to make this book a valuable resource for engineering students.
Thank you and looking forward to your participation!
As we continue to explore, learn, and innovate together, it's essential to take a moment to recognize the remarkable contributions that have sparked engaging discussions, solved perplexing problems, and shared insightful knowledge in the past two weeks. Let's dive into the highlights that have made our community even more vibrant and resourceful.
Burhan Burak brings up an intriguing issue faced when running certain code in MATLAB, seeking advice on how to refactor the code to eliminate a warning message. It's a great example of the practical challenges we often encounter
Jenni asks for guidance on improving linear models to fit data points more accurately. This question highlights the common hurdles in data analysis and model fitting, sparking a conversation on best practices and methodologies.
A thought-provoking question posed by goc3 that delves into the intricacies of MATLAB's logical operations. It's a great discussion starter that tests and expands our understanding of MATLAB's behavior.
Toshiaki Takeuchi shares an insightful visualization of the demand for MATLAB jobs across different regions, based on data from LinkedIn. This post not only provides a snapshot of the job market but also encourages members to discuss trends in MATLAB's use in the industry.
Mike Croucher shares his excitement and insights on two long-awaited features finally making their way into MATLAB R2024a. His post reflects the passion and persistence of our community members in enhancing MATLAB's functionality.
In this informative post, Sivylla Paraskevopoulou offers practical tips for speeding up the training of deep learning models. It's a must-read for anyone looking to optimize their deep learning workflows.
A Heartfelt Thank You 🙏
To everyone who asked a question, started a discussion, or wrote a blog post: Thank you! Your contributions are what make our community a fountain of knowledge, inspiration, and innovation. Let's keep the momentum going and continue to support each other in our journey to explore the vast universe of MATLAB.
Happy Coding!
Note: If you haven't yet, make sure to check out these highlights and add your voice to our growing community. Your insights and experiences are what make us stronger.
You can download these toolkits from the provided links.
The reason for writing this article is that many people have started using the chord diagram plotting toolkit that I developed. However, some users are unsure about customizing certain styles. As the developer, I have a good understanding of the implementation principles of the toolkit and can apply it flexibly. This has sparked the idea of challenging myself to create various styles of chord diagrams. Currently, the existing code is quite lengthy. In the future, I may integrate some of this code into the toolkit, enabling users to achieve the effects of many lines of code with just a few lines.
Without further ado, let's see the extent to which this MATLAB toolkit can currently perform.
Congratulations, @Fangjun Jiang for achieving 10K reputation points.
You reached this milestone by providing valuable contribution to the community since you started answering questions in Since September 2011.
You were very active in the first year, and took some break, but you steadily rose ranks in the recent years to achieve this milestone.
You provided 3954 answers and received 1503 votes. You are ranked #25 in the community. Thank you for your contribution to the community and please keep up the good track record!
In honor of National Pet Day on April 11th, we're excited to announce a fun contest that combines two of our favorite things: our beloved pets and our passion for MATLAB/Simulink! Whether you're a cat enthusiast, a dog lover, or a companion to any other pet, we invite you to join in the fun and showcase your creativity.
How to Participate:
Take a photo of your pet featuring any element of MATLAB/Simulink.
Post it in the Fun channelof the Discussions area.
Include a brief description or story behind the photo - we love to hear about your pets and your creative process!
🏆Prizes:
We will be selecting 3 winners for this contest, and each winner will receive a MathWorks T-shirt or hat! Winners will be chosen based on creativity, originality, and how well they incorporate the MATLAB/Simulink element into their photo.
📅Important Dates:
Contest ends on April 12th, 2024, at 11:59:59 pm, Eastern Time
We can't wait to see all of your adorable and creative pet photos. Let's celebrate National Pet Day in true MathWorks style. Good luck, and most importantly, have fun!
MatGPT was launched on March 22, 2023 and I am amazed at how many times it has been downloaded since then - close to 16,000 downloads in one year. When AI Chat Playground came out on MATLAB Central, I thought surely that people will stop using MatGPT. Boy I was wrong.
In early 2023 I was playing with the new shiny toy called ChatGPT like everyone else but instead of having it tell me jokes or haiku, I wanted to know how I can use it on MATLAB, and I started collecting the prompts that worked. Someone suggested I should turn that into an app, and MatGPT was born with help from other colleagues.
Here is the question - what should I do with it now? Some people suggested I could add other LLMs like Gemini or Claude, but I am more interested in learning how people actually use it.
If you are a MatGPT user, do you mind sharing how you use the app?
I feel like no one at UC San Diego knows this page, let alone this server, is still live. For the younger generation, this is what the whole internet used to look like :)
I was in a meeting the other day and a coworker shared a smiley face they created using the AI Chat Playground. The image looked something like this:
And I suspect the prompt they used was something like this:
"Create a smiley face"
I imagine this output wasn't what my coworker had expected so he was left thinking that this was as good as it gets without manually editing the code, and that the AI Chat Playground couldn't do any better.
I thought I could get a better result using the Playground so I tried a more detailed prompt using a multi-step technique like this:
"Follow these instructions:
- Create code that plots a circle
- Create two smaller circles as eyes within the first circle
- Create an arc that looks like a smile in the lower part of the first circle"
The output of this prompt was better in my opinion.
These queries/prompts are examples of 'zero-shot' prompts, the expectation being a good result with just one query. As opposed to a back-and-forth chat session working towards a desired outcome.
I wonder how many attempts everyone tries before they decide they can't anything more from the AI/LLM. There are times I'll send dozens of chat queries if I feel like I'm getting close to my goal, while other times I'll try just one or two. One thing I always find useful is seeing how others interact with AI models, which is what inspired me to share this.
Does anyone have examples of techniques that work well? I find multi-step instructions often produces good results.
Hello, brilliant minds of our engineering community!
We hope this message finds you in the midst of an exciting project or, perhaps, deep in the realms of a challenging problem, because we've got some groundbreaking news that might just make your day a whole lot more interesting.
🎉 Introducing PreAnswer AI - The Future of Community Support!🎉
Have you ever found yourself pondering over a complex problem, wishing for an answer to magically appear before you even finish formulating the question? Well, wish no more! The MathWorks team, in collaboration with the most imaginative minds from the realms of science fiction, is thrilled to announce the launch of PreAnswer AI, an unprecedented feature set to revolutionize the way we interact within our MATLAB and Simulink community.
What is PreAnswer AI?
PreAnswer AI is our latest AI-driven initiative designed to answer your questions before you even ask them. Yes, you read that right! Through a combination of predictive analytics, machine learning, and a pinch of engineering wizardry, PreAnswer AI anticipates the challenges you're facing and provides you with solutions, insights, and code snippets in real-time.
How Does It Work?
Presentiment Algorithms: By simply logging into MATLAB Central, our AI begins to analyze your recent coding patterns, activity, and even the intensity of your keyboard strokes to understand your current state of mind.
Predictive Insights: Using a complex algorithm, affectionately dubbed "The Oracle", PreAnswer AI predicts the questions you're likely to ask and compiles comprehensive answers from our vast database of resources.
Efficiency and Speed: Imagine the time saved when the answers to your questions are already waiting for you. PreAnswer AI ensures you spend more time innovating and less time searching for solutions.
We are on the cusp of deploying PreAnswer AI in a beta phase and are eager for you to be among the first to experience its benefits. Your feedback will be invaluable as we refine this feature to better suit our community's needs.
Spoiler, it's April 1st if you hadn't noticed. While we might not (yet) have the technology to read minds or predict the future, we do have an incredible community filled with knowledgeable, supportive members ready to tackle any question you throw their way.
Let's continue to collaborate, innovate, and solve complex problems together, proving that while AI can do many things, the power of a united community of brilliant minds is truly unmatched.
Thank you for being such a fantastic part of our community. Here's to many more questions, answers, and shared laughs along the way.
To solve a surface integral for example the over the sphere easily in MATLAB, you can leverage the symbolic toolbox for a direct and clear solution. Here is a tip to simplify the process:
Use Symbolic Variables and Functions: Define your variables symbolically, including the parameters of your spherical coordinates θ and ϕ and the radius r . This allows MATLAB to handle the expressions symbolically, making it easier to manipulate and integrate them.
Express in Spherical Coordinates Directly: Since you already know the sphere's equation and the relationship in spherical coordinates, define x, y, and z in terms of r , θ and ϕ directly.
Perform Symbolic Integration: Use MATLAB's `int` function to integrate symbolically. Since the sphere and the function are symmetric, you can exploit these symmetries to simplify the calculation.
Here’s how you can apply this tip in MATLAB code:
% Include the symbolic math toolbox
syms theta phi
% Define the limits for theta and phi
theta_limits = [0, pi];
phi_limits = [0, 2*pi];
% Define the integrand function symbolically
integrand = 16 * sin(theta)^3 * cos(phi)^2;
% Perform the symbolic integral for the surface integral
I am often talking to new MATLAB users. I have put together one script. If you know how this script works, why, and what each line means, you will be well on your way on your MATLAB learning journey.
% Clear existing variables and close figures
clear;
close all;
% Print to the Command Window
disp('Hello, welcome to MATLAB!');
% Create a simple vector and matrix
vector = [1, 2, 3, 4, 5];
matrix = [1, 2, 3; 4, 5, 6; 7, 8, 9];
% Display the created vector and matrix
disp('Created vector:');
disp(vector);
disp('Created matrix:');
disp(matrix);
% Perform element-wise multiplication
result = vector .* 2;
% Display the result of the operation
disp('Result of element-wise multiplication of the vector by 2:');
disp(result);
% Create plot
x = 0:0.1:2*pi; % Generate values from 0 to 2*pi
y = sin(x); % Calculate the sine of these values
% Plotting
figure; % Create a new figure window
plot(x, y); % Plot x vs. y
title('Simple Plot of sin(x)'); % Give the plot a title
xlabel('x'); % Label the x-axis
ylabel('sin(x)'); % Label the y-axis
grid on; % Turn on the grid
disp('This is the end of the script. Explore MATLAB further to learn more!');
More than 500,000 people have subscribed to the MATLAB channel. MathWorks would like to thank everyone who has taken the time to watch one of our videos, leave us a comment, or share our videos with others. Together we’re accelerating the pace of engineering and science.
March has been bustling with activity on MATLAB Central, bringing forth a treasure trove of insights, innovations, and fun. Whether you're delving into the intricacies of spline conversions or seeking inspiration from Pi Day celebrations, there's something for everyone.
Here’s a roundup of the top posts from the past few weeks that you won't want to miss:
Dive into the technicalities of converting spline forms with a focus on calculating coefficients. A must-read for anyone dealing with spline representations.
Discover the synergy between MATLAB and Visual Studio Code, enhanced by GitHub Copilot support. A game-changer for MATLAB developers.
These threads are just the tip of the iceberg. Each post is a gateway to new knowledge, ideas, and community connections. Dive in, explore, and don't forget to contribute your insights and questions. Together, we make MATLAB Central a vibrant hub of innovation and support.
Firstly, in order to obtain the first n decimal places of pi, we need to write the following code (to prevent inaccuracies, we need to take a few more tails and perform another operation of taking the first n decimal places when needed):
function Pi=getPi(n)
if nargin<1,n=3;end
Pi=char(vpa(sym(pi),n+10));
Pi=abs(Pi)-48;
Pi=Pi(3:n+2);
end
With this function to obtain the decimal places of pi, our visualization journey has begun~Step by step, from simple to complex~(Please try to use newer versions of MATLAB to run, at least R17b)
1 Pie chart
Just calculate the proportion of each digit to the first 1500 decimal places:
Imagine each decimal as a small ball with a mass of
For example, if, the weight of ball 0 is 1, ball 9 is 1.2589, the initial velocity of the ball is 0, and it is attracted by other balls. Gravity follows the inverse square law, and if the balls are close enough, they will collide and their value will become
After adding, take the mod, add the velocity direction proportionally, and recalculate the weight.
The digits of π are shown as a forest. Each tree in the forest represents the digits of π up to the next 9. The first 10 trees are "grown" from the digit sets 314159, 2653589, 79, 3238462643383279, 50288419, 7169, 39, 9, 3751058209, and 749.
BRANCHES
The first digit of a tree controls how many branches grow from the trunk of the tree. For example, the first tree's first digit is 3, so you see 3 branches growing from the trunk.
The next digit's branches grow from the end of a branch of the previous digit in left-to-right order. This process continues until all the tree's digits have been used up.
Each tree grows from a set of consecutive digits sampled from the digits of π up to the next 9. The first tree, shown here, grows from 314159. Each of the digits determine how many branches grow at each fork in the tree — the branches here are colored by their corresponding digit to illustrate this. Leaves encode the digits in a left-to-right order. The digit 9 spawns a flower on one of the branches of the previous digit. The branching exception is 0, which terminates the current branch — 0 branches grow!
LEAVES AND FLOWERS
The tree's digits themselves are drawn as circular leaves, color-coded by the digit.
The leaf exception is 9, which causes one of the branches of the previous digit to sprout a flower! The petals of the flower are colored by the digit before the 9 and the center is colored by the digit after the 9, which is on the next tree. This is how the forest propagates.
The colors of a flower are determined by the first digit of the next tree and the penultimate digit of the current tree. If the current tree only has one digit, then that digit is used. Leaves are placed at the tips of branches in a left-to-right order — you can "easily" read them off. Additionally, the leaves are distributed within the tree (without disturbing their left-to-right order) to spread them out as much as possible and avoid overlap. This order is deterministic.
The leaf placement exception are the branch set that sprouted the flower. These are not used to grow leaves — the flower needs space!
Let's still put the numbers in the form of circles, but the difference is that six numbers are grouped together, and the pure purple circle at the end is the six 9s that we are familiar with decimal places 762-767