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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.
Matt J
Matt J
Ultima attività il 29 Gen 2024

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?
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:
American style football
12%
Soccer / football
39%
baseball
5%
basketball
12%
tennis or golf
7%
rugby, track, cricket, racing, etc.
26%
3712 voti
Congratulations, @Cris LaPierre for achieving 10K reputation points.
You reached this milestone by providing valuable contribution to the community since you started answering questions in Since September 2018.
You provided 3984 answers and received 1142 votes. You are ranked #24 in the community. Thank you for your contribution to the community and please keep up the good track record!
MATLAB Central Team
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
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What amazing animations can be created with no more than 2000 characters of MATLAB code? Check out our GALLERY from the MATLAB Flipbook Mini Hack contest.
Vote on your favorite animations before Dec. 3rd. We will give out MATLAB T-shirts to 10 lucky voters!
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Elija
Elija
Ultima attività il 14 Feb 2024

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
Ultima attività il 28 Nov 2023

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.
I think it would be a really great feature to be able to add an Alpha property to the basic "Line" class in MATLAB plots. I know that I have previously had to resort to using Patch to be able to plot semitransparent lines, but there are also so many other functions that rely on the "Line" class.
For example, if you want to make a scatter plot from a table with things specified into groups, you can use ScatterHistogram or gscatter but since gscatter uses the Line class, you can't adjust the marker transparency. So if you don't want the histograms, you are stuck with manually separating it and using scatter with hold on.
Hi Guys
Posting this based on a thought I had, so I don't really ahve any code however I would like to know if the thought process is correct and/or relatively accurate.
Consider a simple spring mass system which only allows compression on the spring however when there is tension the mass should move without the effect of the spring distrupting it, thus the mass is just thrown vertically upwards.
The idea which I came up with for such a system is to have two sets of dfferential equations, one which represents the spring system and another which presents a mass in motion without the effects of the spring.
Please refer to the below basic outline of the code which I am proposing. I believe that this may produce relatively decent results. The code essentially checks if there is tension in the system if there is it then takes the last values from the spring mass differential equation and uses it as initial conditions for the differential equation with the mass moving wothout the effects of the spring, this process works in reverse also. The error which would exist is that the initial conditions applied to the system would include effects of the spring. Would there be a better way to code such behaviour?
function xp = statespace(t,x,f,c,k,m)
if (k*x(1)) positive #implying tension
**Use last time step as initial conditions**
**differential equation of a mass moving""
end
if x(1) negative #implying that the mass in now moving down therefore compression in spring
**Use last time step as initial conditions**
**differential equation for a spring mass system**
end
end
Seeing a colleague make this mistake (one I've had to fix multiple times in other's work too) makes me want to ask the community: would you like the awgn() function/blocks to give the option for creating a SNR at the bandwidth of the signal? Your typical flow is something like this:
  • Create a signal, usually at some nominal upsampling factor (e.g., 4) such that it's now nicely over sampled, especially if you're using a RRC or similar pulse shaping filter.
  • Potentially add a frequency offset (which might make the sample frequency even higher)
  • Add AWGN channel model for a desired SNR
  • Put this into your detector/receiver model
The problem is, when someone says, "I'm detecting XYZ at foo SNR," it should not magically improve as a function of the oversample. The problem isn't that awgn() generates white noise, that's what it's supposed to do and the typical receiver has noise across the entire band. The problem is that SNR is most properly defined as the signal power over the noise power spectral density times the signal's noise equivalent bandwidth. Now I looked and there's no handy function for computing NEBW for an input signal (there's just a function for assessing analysis windows). In practice it can get a bit tricky. The occupied bandwidth or HPBW are often close enough to the NEBW, we're usually not haggling over hundredths of a dB. So, in my not so humble opinion, the "measured" flag for awgn() should give an option for bandwidth matching or at least document the behavior better in the help page. All too often I'm seeing 3-6 (or worse) dB errors because people aren't taking the signal's bandwidth into account.
LAWAN HARUNA
LAWAN HARUNA
Ultima attività il 6 Nov 2023

good afternoon everyone my name is Dundu lawan haruna ,i'm a final year student at the department of computer engineering ABU Zaria, Nigerian , and i wanted to do my final year project based on computer vision : project topic , designing an eye glasses to help those people with visual imparement to be able to navigate enviroment efficiently , that's why i need a support from you guys ,all advised are highly well come , thank you for your support.
You are invited to join our 2023 community contest – MATLAB Flipbook Mini Hack! This year’s contest revolves around creating interesting animations using MATLAB.
Whether you are a seasoned MATLAB user or just getting started, this contest offers a fantastic opportunity to showcase your skills, learn from others, and engage with the vibrant MATLAB Central community.
Timeframe
This contest runs for 4 weeks from Nov. 6th to Dec. 3rd.
How to play
  • Create a new animation or remix an existing one with up to 2,000 characters of code.
  • Simply vote on the animations 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.
Check out the gallery and vote on the animations you like.
The MATLAB Central Community team
Image Analyst
Image Analyst
Ultima attività il 31 Ott 2023

Just in time for Halloween.