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AHD
AHD
Last activity 大约 4 小时 前

Hello,
Anyone has basic MATLAB code upon RSMA i.e. to understand basic implementation of RSMA, how to generate common and private messages in MATLAB, etc...?

Mike Croucher
Mike Croucher
Last activity 2024-12-6,22:32

Many of my best friends at MathWorks speak Spanish as their first language and we have a large community of Spanish-speaking users. You can see good evidence of this by checking out our relatively new Spanish YouTube channel which recently crossed the 10,000 subscriber mark
Mike Croucher
Mike Croucher
Last activity 2024-12-5,17:25

I've always used MATLAB with other languages. In the early days, C and C++ via mex files were the most common ways I spliced two languages together. Other than that I've also used MATLAB with Java, Excel and even Fortran.
In more recent years, Python is the language I tend to use most alongside MATLAB and support for this combination is steadily improving. In my latest blog post, I show how easy it has become to use Python's Numpy with MATLAB.
Have you used this functionality much? If so, what for? How well did it work for you?
I am inspired by the latest video from YouTube science content creator Veritasium on his distinct yet thorough explanation on how rainbows work. In his video, he set up a glass sphere experiment representing how light rays would travel inside a raindrop that ultimately forms the rainbow. I highly recommend checking it out.
In the meantime, I created an interactive MATLAB App in MATLAB Online using App Designer to visualize the light paths going through a spherical raindrop with numerical calculations along the way. While I've seen many diagrams out there showing the light paths, I haven't found any doing calculations in each step. Hence I created an app in MATLAB to show the calculations along with the visualizations as one varies the position of the incoming light ray.
Demo video:
For more information about the app and how to open it and play around with it in MATLAB Online, please check out my blog article:
Our MathWorks Usability Team is working on an accessibility project and they want to interview people who use MATLAB and also have experience with screen readers.
If you fit the criteria and are interested, sign up here https://www.mathworks.com/products/usability.html?tfa_30=A11Y
I wish I knew more about the intended evolution of the capabilities of the function arguments block. I love implementing function syntaxes using this relatively new form, but it doesn't yet handle some function syntax design patterns that I think are valuable and worth keeping.
For example, some functions take an input quantity that can something numeric, or it can be an option string that descriptively names a particular value of that quantity. One example is dateshift(t,"dayofweek",dow), where dow can be an integer from 1 to 7, or it can be one of the option strings "weekday" or "weekend".
Another example is Image Processing Toolbox that take a connectivity specifier as input. The function bwconncomp is one particular case. Connectivity can be specified using certain scalars, certain arrays, or the option string "maximal".
I think this is a worthwhile function design pattern, but I don't think the arguments block validation functionality supports it well (unless you use a lot of extra code that duplicates standard MATLAB behavior, which undermines the value of the arguments block).
I posted about this today over on my blog. See "Function Syntax Design Conundrum."
MathWorkers - believe me, I know that it is not in your DNA to discuss future features. But would anyone care to offer a hint about directions for the arguments block functionality?
Hi! My name is Mike McLernon, and I’m a product marketing engineer with MathWorks. In my role, I look at the trends ongoing in the wireless industry, across lots of different standards (think 5G, WLAN, SatCom, Bluetooth, etc.), and I seek to shape and guide the software that MathWorks builds to respond to these trends. That’s all about communicating within the Mathworks organization, but every so often it’s worth communicating these trends to our audience in the world at large. Many of the people reading this are engineers (or engineers at heart), and we all want to know what’s happening in the geek world around us. I think that now is one of these times to communicate an important milestone. So, without further ado . . .
Bluetooth 6.0 is here! Announced in September by the Bluetooth Special Interest Group (SIG), it’s making more advances in its quest to create a “world without wires”. A few of the salient features in Bluetooth 6.0 are:
  1. Channel sounding (for accurate distance measurements)
  2. Decision-based advertising filtering (for more efficient channel scanning)
  3. Monitoring advertisers (for improved energy efficiency when devices come into and go out of range)
  4. Frame space updates (for both higher throughput and better coexistence management)
Bluetooth 6.0 includes other features as well, but the SIG has put special promotional emphasis on channel sounding (CS), which once upon a time was called High Accuracy Distance Measurement (HADM). The SIG has said that CS is a step towards true distance awareness, and 10 cm ranging accuracy. I think their emphasis is in exactly the right place, so let’s learn more about this technology and how it is used.
CS can be used for the following use cases:
  1. Keyless vehicle entry, performed by communication between a key fob or phone and the car’s anchor points
  2. Smart locks, to permit access only when an authorized device is within a designated proximity to the locks
  3. Geofencing, to limit access to designated areas
  4. Warehouse management, to monitor inventory and manage logistics
  5. Asset tracking for virtually any object of interest
In the past, Bluetooth devices would use a received signal strength indicator (RSSI) measurement to infer the distance between two of them. They would assume a free space path loss on the link, and use a straightforward equation to estimate distance:
where
received power in dBm,
transmitted power in dBm,
propagation loss in dB,
distance between the two devices, in m,
Bluetooth signal wavelength, in m,
Bluetooth signal frequency, in Hz,
speed of light (3 x 1e8 m/s).
So in this method, . But if the signal suffers more loss from multipath or shadowing, then the distance would be overestimated. Something better needed to be found.
Bluetooth 6.0 introduces not one, but two ways to accurately measure distance:
  1. Round-trip time (RTT) measurement
  2. Phase-based ranging (PBR) measurement
The RTT measurement method uses the fact that the Bluetooth signal time of flight (TOF) between two devices is half the RTT. It can then accurately compute the distance d as
, where c is again the speed of light. This method requires accurate measurements of the time of departure (TOD) of the outbound signal from device 1 (the Initiator), time of arrival (TOA) of the outbound signal to device 2 (the Reflector), TOD of the return signal from device 2, and TOA of the return signal to device 1. The diagram below shows the signal paths and the times.
If you want to see how you can use MATLAB to simulate the RTT method, take a look at Estimate Distance Between Bluetooth LE Devices by Using Channel Sounding and Round-Trip Timing.
The PBR method uses two Bluetooth signals of different frequencies to measure distance. These signals are simply tones – sine waves. Without going through the derivation, PBR calculates distance d as
, where
distance between the two devices, in m,
speed of light (3 x 1e8 m/s),
phase measured at the Initiator after the tone at completes a round trip, in radians,
phase measured at the Initiator after the tone at completes a round trip, in radians,
frequency of the first tone, in Hz,
frequency of the second tone, in Hz.
The mod() operation is needed to eliminate ambiguities in the distance calculation and the final division by two is to convert a round trip distance to a one-way distance. Because a given phase difference value can hold true for an infinite number of distance values, the mod() operation chooses the smallest distance that satisfies the equation. Also, these tones can be as close as 1 MHz apart. In that case, the maximum resolvable distance measurement is about 150 m. The plot below shows that ambiguity and repetition in distance measurement.
If you want to see how you can use MATLAB to simulate the PBR method, take a look at Estimate Distance Between Bluetooth LE Devices by Using Channel Sounding and Phase-Based Ranging.
Bluetooth 6.0 outlines RTT and PBR distance measurement methods, but CS does not mandate a specific algorithm for calculating distance estimates. This flexibility allows device manufacturers to tailor solutions to various use cases, balancing computational complexity with required accuracy and adapting to different radio environments. Examples include simple phase difference calculations and FFT-based methods.
Although Bluetooth 6.0 is now out, it is far from a finished version. The SIG is actively working through the ratification process for two major extensions:
  1. High Data Throughput, up to 8 Mbps
  2. 5 and 6 GHz operation
See the last few minutes of this video from the SIG to learn more about these exciting future developments. And if you want to see more Bluetooth blogs, give a review of this one! Finally, if you have specific Bluetooth questions, give me a shout and let’s start a discussion!
Image Analyst
Image Analyst
Last activity 2024-12-2,22:14

Christmas season is underway at my house:
(Sorry - the ornament is not available at the MathWorks Merch Shop -- I made it with a 3-D printer.)
So I made this.
clear
close all
clc
% inspired from: https://www.youtube.com/watch?v=3CuUmy7jX6k
%% user parameters
h = 768;
w = 1024;
N_snowflakes = 50;
%% set figure window
figure(NumberTitle="off", ...
name='Mat-snowfalling-lab (right click to stop)', ...
MenuBar="none")
ax = gca;
ax.XAxisLocation = 'origin';
ax.YAxisLocation = 'origin';
axis equal
axis([0, w, 0, h])
ax.Color = 'k';
ax.XAxis.Visible = 'off';
ax.YAxis.Visible = 'off';
ax.Position = [0, 0, 1, 1];
%% first snowflake
ht = gobjects(1, 1);
for i=1:length(ht)
ht(i) = hgtransform();
ht(i).UserData = snowflake_factory(h, w);
ht(i).Matrix(2, 4) = ht(i).UserData.y;
ht(i).Matrix(1, 4) = ht(i).UserData.x;
im = imagesc(ht(i), ht(i).UserData.img);
im.AlphaData = ht(i).UserData.alpha;
colormap gray
end
%% falling snowflake
tic;
while true
% add a snowflake every 0.3 seconds
if toc > 0.3
if length(ht) < N_snowflakes
ht = [ht; hgtransform()];
ht(end).UserData = snowflake_factory(h, w);
ht(end).Matrix(2, 4) = ht(end).UserData.y;
ht(end).Matrix(1, 4) = ht(end).UserData.x;
im = imagesc(ht(end), ht(end).UserData.img);
im.AlphaData = ht(end).UserData.alpha;
colormap gray
end
tic;
end
ax.CLim = [0, 0.0005]; % prevent from auto clim
% move snowflakes
for i = 1:length(ht)
ht(i).Matrix(2, 4) = ht(i).Matrix(2, 4) + ht(i).UserData.velocity;
end
if strcmp(get(gcf, 'SelectionType'), 'alt')
set(gcf, 'SelectionType', 'normal')
break
end
drawnow
% delete the snowflakes outside the window
for i = length(ht):-1:1
if ht(i).Matrix(2, 4) < -length(ht(i).Children.CData)
delete(ht(i))
ht(i) = [];
end
end
end
%% snowflake factory
function snowflake = snowflake_factory(h, w)
radius = round(rand*h/3 + 10);
sigma = radius/6;
snowflake.velocity = -rand*0.5 - 0.1;
snowflake.x = rand*w;
snowflake.y = h - radius/3;
snowflake.img = fspecial('gaussian', [radius, radius], sigma);
snowflake.alpha = snowflake.img/max(max(snowflake.img));
end
Is it possible to differenciate the input, output and in-between wires by colors?
At the present time, the following problems are known in MATLAB Answers itself:
  • @doc is presenting messed up text until something is selected
  • Symbolic output is not displaying. The work-around is to disp(char(EXPRESSION))
  • Near the top of each Question is displayed a link of the most recent activity on the question. The link is normally clickable and takes you directly to the relevant contribution. But at the moment the link does not take you anywhere
Chen Lin
Chen Lin
Last activity 大约 20 小时 前

Hello, MATLAB fans!
For years, many of you have expressed interest in getting your hands on some cool MathWorks merchandise. I'm thrilled to announce that the wait is over—the MathWorks Merch Shop is officially open!
In our shop, you'll find a variety of exciting items, including baseball caps, mugs, T-shirts, and YETI bottles.
Visit the shop today and explore all the fantastic merchandise we have to offer. Happy shopping!
I was curious to startup your new AI Chat playground.
The first screen that popped up made the statement:
"Please keep in mind that AI sometimes writes code and text that seems accurate, but isnt"
Can someone elaborate on what exactly this means with respect to your AI Chat playground integration with the Matlab tools?
Are there any accuracy metrics for this integration?
Just shared an amazing YouTube video that demonstrates a real-time PID position control system using MATLAB and Arduino.
All files, including code and setup details, are available on GitHub. Check it out!
I don't like the change
16%
I really don't like the change
29%
I'm okay with the change
24%
I love the change
11%
I'm indifferent
11%
I want both the web & help browser
11%
38 个投票
We are thrilled to announce the grand prize winners of our MATLAB Shorts Mini Hack contest! This year, we invited the MATLAB Graphics and Charting team, the authors of the MATLAB functions used in every entry, to be our judges. After careful consideration, they have selected the top three winners:
1st place - Tim
Judge comments: Realism & detailed comments; wowed us with Manta Ray
2nd place – Jenny Bosten
Judge comments: Topical hacks : Auroras & Wind turbine; beautiful landscapes & nightscapes
3rd place - Vasilis Bellos
Judge comments: Nice algorithms & extra comments; can’t go wrong with Pumpkins
There is also an Honorable Mention - William Dean
Judge comments: Impressive spring & cubes!
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!
You can make a lot of interesting objects with matlab primitive shapes (e.g. "cylinder," "sphere," "ellipsoid") by beginning with some of the built-in Matlab primitives and simply applying deformations. The gif above demonstrates how the Manta animation was created using a cylinder as the primitive and successively applying deformations: (https://www.mathworks.com/matlabcentral/communitycontests/contests/8/entries/16252);
Similarly, last year a sphere was deformed to create a face in two of my submissions, for example, the profile in "waking":
You can piece-wise assemble images, but one of the advantages of creating objects with deformations is that you have a parametric representation of the surface. Creating a higher or lower polygon rendering of the surface is as simple as declaring the number of faces in the orignal primitive. For example here is the scene in "snowfall" using sphere with different numbers of input faces:
sphere(100)
sphere(500)
High poly models aren't always better. Low-polygon shapes can sometimes add a little distance from that low point in the uncanny valley.