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American style football
12%
Soccer / football
39%
baseball
5%
basketball
12%
tennis or golf
7%
rugby, track, cricket, racing, etc.
26%
3712 voti
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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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Kali
Kali
Ultima attività il 21 Dic 2023

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.
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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.
I saw this post on Answers.
I was impressed at the capability of the AI, as I have been at other times when I posed a question to it, at least some of the time. So much so that I wondered...
What if the AI were automatically applied to EVERY question on Answers? Would that be a good or bad thing? For example, suppose the AI automatically offers an answer to every question as soon as it gets posted? Of course, users would still be allowed to post their own, possibly better answers. But would it tend to disincentivise individuals from ansering questions?
Perhaps as bad, would it push Answers into the mode of a homework solving forum? Since if every homework question gets a possibly pretty good automatic AI generated solution, then every student will just post all HW questions, and the forum would quickly become overwhelmed.
I suppose one idea could be to set up the AI to post an answer to all un-answered questions that are at least one month old. Then students would not gain by posting their homework.
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.
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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.
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Image Analyst
Image Analyst
Ultima attività il 31 Ott 2023

Just in time for Halloween.
I rarely/never save .fig files
47%
Continue working on it later
16%
Archive for future reference
23%
Share within my organization
10%
Share outside my organization
2%
Other (please leave a comment)
2%
2097 voti
Julian
Julian
Ultima attività il 5 Feb 2024

I know the latest version of MATLAB R2023b has this feature already, put it should be added to R2023a as well because of its simplicity and convenience.
Basically, I want to make a bar graph that lets me name each column in a basic bar graph:
y=[100 99 100 200 200 300 500 800 1000];
x=["0-4" "5-17" "18-29" "30-39" "40-49" "50-64" "65-74" "75-84" "85+"];
bar(x,y)
However, in R2023a, this isn't a feature. I think it should be added because it helps to present data and ideas more clearly and professionally, which is the purpose of a graph to begin with.