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We are thrilled to announce that every community member now has the ability to create a poll in Discussions, allowing you to gather votes and opinions from the community.
How to create a poll:
You can find the ‘Create a Poll’ link just below the text box (see screenshot below). Please note that the default type of content is a ‘Discussion’. To start a poll, simply click the link.
Creating a poll is straightforward. You can add up to 6 choices for your poll and set the duration from 1 to 6 weeks.
Where to find the poll
Polls created by community members will appear only in the channel where they are created and the landing page of Discussions area. Discussions moderators have the privilege to feature/broadcast the poll across Answers, File Exchange, and Cody.
Thoughts?
We can’t wait to see what interesting polls our community will create. Meanwhile, if you have any questions or suggestions, feel free to leave a comment.
We're excited to announce that the 2024 Community Contest—MATLAB Shorts Mini Hack starts today! The contest will run for 5 weeks, from Oct. 7th to Nov. 10th.
What creative short movies will you create? Let the party begin, and we look forward to seeing you all in the contest!
If you are interested in AI, Autonomous Systems and Robotics, and the future of engineering, don't miss out on MATLAB EXPO 2024 and register now.
You will have the opportunity to connect with engineers, scientists, educators, and researchers, and new ideas.
Featured Sessions:
- From Embedded to Empowered: The Rise of Software-Defined Products - María Elena Gavilán Alfonso, MathWorks
- The Empathetic Engineers of Tomorrow - Dr. Darryll Pines, University of Maryland
- A Model-Based Design Journey from Aerospace to an Artificial Pancreas System - Louis Lintereur, Medtronic Diabetes
Featured Topics:
- AI
- Autonomous Systems and Robotics
- Electrification
- Algorithm Development and Data Analysis
- Modeling, Simulation, Verification, Validation, and Implementation
- Wireless Communications
- Cloud, Software Factories, and DevOps
- Preparing Future Engineers and Scientists
We are thrilled to announce the redesign of the Discussions leaf page, with a new user-focused right-hand column!
Why Are We Doing This?
- Address Readers’ Needs:
Previously, the right-hand column displayed related content, but feedback from our community indicated that this wasn't meeting your needs. Many of you expressed a desire to read more posts from the same author but found it challenging to locate them.
With the new design, readers can easily learn more about the author, explore their other posts, and follow them to receive notifications on new content.
- Enhance Authors’ Experience:
Since the launch of the Discussions area earlier this year, we've seen an influx of community members sharing insightful technical articles, use cases, and ideas. The new design aims to help you grow your followers and organize your content more effectively by editing tags. We highly encourage you to use the Discussions area as your community blogging platform.
We hope you enjoy the new design of the right-hand column. Please feel free to share your thoughts and experiences by leaving a comment below.
Dear contest participants,
The 2024 Community Contest—MATLAB Shorts Mini Hack—is just one week away! Last year, we challenged you to create a 48-frame, 2-second animation. This year, we're doubling the fun by increasing the frame count to 96 and adding audio support. Your mission? Create a short movie!
As always, whether you are a seasoned MATLAB user or just a beginner, you can participate in the contest and have opportunities to win amazing prizes.
Timeframe:
- The contest will run for 5 weeks, from Oct. 7th to Nov. 10th, Eastern Time.
General Rules:
- The first week is dedicated to entry creation, and the fifth week is reserved for voting only.
- Create a 96-frame, 4-second animation and add audio. We will loop it 3 times to create a 12-second short movie for you.
- The character limit remains at 2,000 characters.
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.
Warm-up!
With one week left before the contest begins, we recommend you warm up by reading a fantastic article: Walkthrough: making Little Nemo's airship in MATLAB by @Tim. The article shares both technical insights and the challenges encountered along the way.
The MATLAB Central Community Team
We are excited to invite you to join our 2024 community contest – MATLAB Shorts Mini Hack! Last year, we challenged you to create a 48-frame animation. In 2024, we are increasing the frame count to 96 and supporting audio. Your mission? Create a short movie!
Whether you are a seasoned MATLAB user or just a beginner, you can participate in the contest and have opportunities to win amazing prizes. Be sure to check out our Blog post for more details on the Community Contests.
Timeframe
This contest runs for 5 weeks, from Oct. 7th to Nov. 10th.
How to Participate
- Create a new short movie or remix an existing one with up to 2,000 characters of code.
- Vote or comment on the short movies 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.
Stay Informed
Make sure to follow the contest to get important announcements and your prize updates.
The AI Chat Playground at MATLAB Central has two new upgrades: OpenAI GPT-4o mini and MATLAB R2024b!
GPT-4o mini is a new language model from OpenAI and brings general knowledge up to October 2023. GPT-4o mini surpasses GPT-3.5 Turbo and other small models on academic benchmarks across both textual intelligence and reasoning. Our goal is to keep improving the output of the AI Chat Playground. This upgrade is available now: https://www.mathworks.com/matlabcentral/playground/
One more thing... we also updated the system to the latest release of MATLAB. This is R2024b and comes with hundreds of updates and new plot types to explore.Check out Mike Croucher's blog post about the latest version of MATLAB: https://blogs.mathworks.com/matlab/2024/09/13/the-latest-version-of-matlab-r2024b-has-just-been-released/
We are looking forward to your feedback on the updates to the AI Chat Playground. Let us know what you think and how you use this community app.
Always!
29%
It depends
14%
Never!
21%
I didn't know that was possible
36%
1810 votes
Hello! I'm working on a project that involves training an LSTM (or GRU) model with time-series data. My data consists of 2 features (strain and deflection) over 5 time steps. I am getting the following error:
Error using trainNetwork: The training sequences are of feature dimension 8 5 but the input layer expects sequences of feature dimension 2.
Here's a breakdown of the data:
- XTrain has dimensions: [8, 5, 2] (8 sequences, 5 time steps, 2 features).
- I'm reshaping the data to [sequenceLength, numFeatures, numSequences] using permute(XTrain, [2, 3, 1]).
- YTrain has dimensions: [8, 2] (8 sequences, 2 output values).
I'm using the following layer configuration:
layers = [ ...
sequenceInputLayer(2) % 2 features: strain and deflection
lstmLayer(100, 'OutputMode', 'last') % LSTM layer
fullyConnectedLayer(2) % Output layer for 2 values: strain and deflection
regressionLayer];
What am I missing? How should I format the input data to make this work with trainNetwork?
Hi everyone,
I need someone to assist me toward simulating real-time IoT data collection using ThinkSpeak on online kaggle datasets
Hello everyone,
Over the past few weeks, our community members have shared some incredible insights and resources. Here are some highlights worth checking out:
Interesting Questions
Johnathan is seeking help with implementing a complex equation into MATLAB's curve fitting toolbox. If you have experience with curve fitting or MATLAB, your input could be invaluable!
Popular Discussions
Athanasios continues his exploration of the Duffing Equation, delving into its chaotic behavior. It's a fascinating read for anyone interested in nonlinear dynamics or chaos theory.
John shares his playful exploration with MATLAB to find a generative equation for a sequence involving Fibonacci numbers. It's an intriguing challenge for those who love mathematical puzzles.
From File Exchange
Ayesha provides a graphical analysis of linearised models in epidemiology, offering a detailed look at the dynamics of these systems. This resource is perfect for those interested in mathematical modeling.
Gareth brings some humor to MATLAB with a toolbox designed to share jokes. It's a fun way to lighten the mood during conferences or meetups.
From the Blogs
Ned Gulley interviews Tim Marston, the 2023 MATLAB Mini Hack contest winner. Tim's creativity and skills are truly inspiring, and his story is a must-read for aspiring programmers.
Sivylla discusses the integration of AI with embedded systems, highlighting the benefits of using MATLAB and Simulink. It's an insightful read for anyone interested in the future of AI technology.
Thank you to all our contributors for sharing your knowledge and creativity. We encourage everyone to engage with these posts and continue fostering a vibrant and supportive community.
Happy exploring!
Explore the newest online training courses, available as of 2024b: one new Onramp, eight new short courses, and one new learning path. Yes, that’s 10 new offerings. We’ve been busy.
As a reminder, Onramps are free to all. Short courses and learning paths require a subscription to the Online Training Suite (OTS).
- Multibody Simulation Onramp
- Analyzing Results in Simulink
- Battery Pack Modeling
- Introduction to Motor Control
- Signal Processing Techniques for Streaming Signals
- Core Signal Processing Techniques in MATLAB (learning path – includes the four short courses listed below)
Local large language models (LLMs), such as llama, phi3, and mistral, are now available in the Large Language Models (LLMs) with MATLAB repository through Ollama™!
Read about it here:
%I encountered the following problem in the calculation: 1. The calculated H is negative, %and I am unsure if the calculation is correct. Some formulas cannot be simplified and still %exist in the form of 5000/51166. 3. Poor overall code fluency
clear all
close
%% 参数定义parameter definition
P = 42;
c = 800;
E = 15000000;
K = 1.8;
P_ya = 18000;
F = 2;
y = 26.8;
R = 20; % radius
syms H B
%H=100;
% 计算破裂角 a Calculate the rupture angle
if K <= 0.5
a = 90;
elseif K <= 1
a = -90 * K + 135;
elseif K <= 3
a = -22.5 * K + 67.5;
else
a = 0;
end
% 显示计算得到的 a 的值
disp(['当 K = ', num2str(K), ' 时，破裂角 a = ', num2str(a), '°']);
%% 求解初始破裂角相关量 Solving the initial rupture angle related quantities
L = H + R * (1 - sind(a));
G_1 = (y * L^2) / (2 * tand(B)); % 三角形块体的自重
p = atan2(tand(P), F); % 折减后的内摩擦角
C = c * L; % 竖直面上粘聚力合力
C_s = c * L / (F * sind(B)); % 破裂面上粘聚力合力
G_0 = 2 * y * H * cosd(a);
z = 0.9 * P; % 按照围岩等级取值，三级围岩取0.9
%% 定义目标函数 E(B) Define the objective function E (B)
%E_func = @(B) (y ./ (2 .* tand(B))) .* sind(B + p) ./ cosd(B + p - z);
E_func=@(B) (cosd(B+p).*sind(B)).*cosd(B).*cosd(B+p-z)+sind(B+p).*sind(B).*(sind(B+p-z).*cosd(B)+cosd(B+p-z).*sind(B));
%% 数值求导函数 Numerical derivative function
% 使用中心差分法计算导数
dE_func = @(B) (E_func(B + 1e-6) - E_func(B - 1e-6)) / (2e-6);
%% 数值寻找导数为零的 B 值
% 只寻找一个接近的 B 值
B_range = [0, 90]; % B 的取值范围
B_init = 45; % 初始猜测值，设置为 45 度
% 使用 fzero 寻找导数为零的 B 值
try
B_zero = fzero(dE_func, B_init);
% 检查找到的 B 值是否满足条件
if abs(dE_func(B_zero)) < 1e-6
disp(['找到满足条件的 B 值为：', num2str(B_zero)]);
else
disp('没有找到导数接近零的 B 值');
end
catch
disp('fzero 计算失败，未找到满足条件的 B 值');
end
B=B_zero
%% 计算埋深 Calculate burial depth
f1 = ((G_1 - C) .* sind(p + B_zero) + C_s .* cosd(p)) ./ cosd(B_zero + p - z);
f2 = (P_ya - G_0 - 2 .* C) / (2 * sind(z));
% 定义控制方程，解出 H
eqn = f1 - f2 == 0;
% 使用 solve 反解出 H
sol_H_sym = solve(eqn, H);
% 将符号解转换为具体的数值
sol_H_num = double(subs(sol_H_sym));
% 显示结果
disp(['解出的 H 的值为：', num2str(sol_H_num)]);
Dear MATLAB contest enthusiasts,
In the 2023 MATLAB Mini Hack Contest, Tim Marston captivated everyone with his incredible animations, showcasing both creativity and skill, ultimately earning him the 1st prize.
We had the pleasure of interviewing Tim to delve into his inspiring story. You can read the full interview on MathWorks Blogs: Community Q&A – Tim Marston.
Last question: Are you ready for this year’s Mini Hack contest?
I was browsing the MathWorks website and decided to check the Cody leaderboard. To my surprise, William has now solved 5,000 problems. At the moment, there are 5,227 problems on Cody, so William has solved over 95%. The next competitor is over 500 problems behind. His score is also clearly the highest, approaching 60,000.
I've been working on some matrix problems recently(Problem 55225)
and this is my code
It turns out that "Undefined function 'corr' for input arguments of type 'double'." However, should't the input argument of "corr" be column vectors with single/double values? What's even going on there?
Hi,
I need to know how to resolve EDO System with MATLAB. The system has this structure:
A*x̄' + B*x̄ + C = 0
A, B are square matrix with constant coefficients. Example: A = [a b; c d]; and B = [e f; g h];
C is the constant vector transposed. Example: C = [i j]';
x̄ is the vector transposed of the variables/functions I need to find. Example: x̄ = [x1 x2]';
x̄' is the vector transposed of the derivative of the variables/functions I need to find. Example: x̄' = [dx1/dt dx2/dt]';
The example is made for a EDO System of 2 differential equations. But It would be interesting if MATLAB could resolve a n x n matrix.
Any suggestion?
Hello,
I am using BEAR TOOLBOX to obtain impulse response function of outcome variable to the 25 basis point monetary policy shock. The problem is there is no option in App of BEAR toolbox. how can i do it . please suggest
Hello everybody. I'm using Newton's method to solve a liner equation whose solution should be in [0 1]. Unfortunately, the coe I'm using gives NaN as a result for a specific combination of parameters and I would like to understand if I can improve the code I wrote for my Newton's method. In the specific case I'm considering, I reach the maximum iterations even if the tolerance is very low.
function [x,n,ier] = newton(f,fd,x0,nmax,tol)
% Newton's method for non-linear equations
ier = 0;
for n = 1:nmax
x = x0-f(x0)/fd(x0);
if abs(x-x0) <= tol
ier = 1;
break
end
x0 = x;
end
% % % % Script for solving NaN
mNAN= 16.1;
lNAN= 10^-4;
f= @(x) mNAN*x+lNAN*exp(mNAN*x)-lNAN*exp(mNAN);
Fd= @(x) mNAN*(1+lNAN*exp(mNAN*x));
tolNaN=10^-1;
nmax=10^8;
AB0 = 0.5;
[amNAN,nNAN,ierNAN]=newton(f,Fd,AB0,nmax,tolNaN);
amNAN
Llimit=f(0)
Ulimit=f(1)
fplot(@(x) mNAN*x+lNAN*exp(mNAN*x)-lNAN*exp(mNAN),[0 1.1])
