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20 Oct 2014 Random Walk Demonstrates concept of a random walk Author: Alex Dytso mostafa khalili

19 Sep 2014 LMMSE Equalizer Implementation of LMMSE (linear minimum mean square error) Equalizer used to combat ISI Author: Alex Dytso Alex Dytso

What do you mean? It's here. Just download it

19 Sep 2014 LMMSE Equalizer Implementation of LMMSE (linear minimum mean square error) Equalizer used to combat ISI Author: Alex Dytso S R M Universiry

Please send me the lmmse program.

14 May 2014 Extended Kalman Filter Tracking Object in 3-D Using Kalman filter to track object in 3D. Comparing Extended Kalman filter to its linear version. Author: Alex Dytso Ahsan

I give the X(:,1)=MAT(1,:)' as actual initial condition, where MAT is the matrix of [501x6] and i'm confusing about initial observation `Z` and assumed initial condition `Xh`

14 May 2014 Extended Kalman Filter Tracking Object in 3-D Using Kalman filter to track object in 3D. Comparing Extended Kalman filter to its linear version. Author: Alex Dytso Ahsan

The value of Z is unused from argument in proccesANDobserve and Jacobian function.

14 May 2014 Extended Kalman Filter Tracking Object in 3-D Using Kalman filter to track object in 3D. Comparing Extended Kalman filter to its linear version. Author: Alex Dytso Ahsan

I know this is the observation vector, I edited a bit of your code for my purpose, but it crosses the actual trajectory and calculating in its opposite way. I have a matrix `MAT` of [501x6] having 1:3 for position and 4:6 for velocities, How can I set the initial observation vector and also what other initial assumptions would be set?

07 May 2014 Extended Kalman Filter Tracking Object in 3-D Using Kalman filter to track object in 3D. Comparing Extended Kalman filter to its linear version. Author: Alex Dytso Alex Dytso

'Z' Stands for the observation vector and it is used in number of places for example when you compute quantity called innovation.

07 May 2014 Extended Kalman Filter Tracking Object in 3-D Using Kalman filter to track object in 3D. Comparing Extended Kalman filter to its linear version. Author: Alex Dytso Ahsan

Hello, I didn't understand the Use of `Z` as this is unused in your code. Its always calculating but didn't use the initial array.

13 Apr 2014 Distributive Power Control Algorithm This code is a simulation of 3 user Distributed Power Control algorithm used in CDMA networks Author: Alex Dytso fibrlink,com lu

05 Feb 2014 Zero Forcing Equalizer Simulation This code is demonstrates implementation of Zero Forcing Equalizer in a communication channel Author: Alex Dytso Liping Wang

01 Feb 2014 Scalar Kalman Filter This code serves as a tutorial for implementation of Scalar Kalman Filter Author: Alex Dytso Ananad B

a

20 Nov 2013 Distributive Power Control Algorithm This code is a simulation of 3 user Distributed Power Control algorithm used in CDMA networks Author: Alex Dytso jeffin

good

30 Sep 2013 Extended Kalman Filter Tracking Object in 3-D Using Kalman filter to track object in 3D. Comparing Extended Kalman filter to its linear version. Author: Alex Dytso yatie SUAIB

ok,thank you very much

26 Sep 2013 Extended Kalman Filter Tracking Object in 3-D Using Kalman filter to track object in 3D. Comparing Extended Kalman filter to its linear version. Author: Alex Dytso Alex Dytso

Yes, here is the document this is based on
https://dl.dropboxusercontent.com/u/12025879/Extended%20Kalman%20Filter.pdf

26 Sep 2013 Extended Kalman Filter Tracking Object in 3-D Using Kalman filter to track object in 3D. Comparing Extended Kalman filter to its linear version. Author: Alex Dytso yatie SUAIB

Hi Alex
Do you have the article/journal paper that you are referring to in order to write these Matlab codes?

31 Mar 2013 Extended Kalman Filter Tracking Object in 3-D Using Kalman filter to track object in 3D. Comparing Extended Kalman filter to its linear version. Author: Alex Dytso Alex Dytso

In order to convert to 2-D you just have to change the appropriate dimensions of matrices. You can also use the code as is and ignore one of the outputs.

31 Mar 2013 Extended Kalman Filter Tracking Object in 3-D Using Kalman filter to track object in 3D. Comparing Extended Kalman filter to its linear version. Author: Alex Dytso Atef

please how apply this code for 2-D ?

19 Feb 2013 LMMSE Equalizer Implementation of LMMSE (linear minimum mean square error) Equalizer used to combat ISI Author: Alex Dytso Alex Dytso

Please Comment

19 Feb 2013 Three way Dual Probability This code simulates a dual between 3 players and compares two strategies Author: Alex Dytso Alex Dytso

Please add comments

30 Dec 2012 Extended Kalman Filter Tracking Object in 3-D Using Kalman filter to track object in 3D. Comparing Extended Kalman filter to its linear version. Author: Alex Dytso W. Chong

15 Jun 2012 Grouping of 2 function Function that generates all possible groups of 2 Author: Alex Dytso Alex Dytso

Thank you for your response. This is exactly the reason why I made this post. In my opinion MatLab needs a better combinatorial package. So stimulating discussion on it is very important in my opinion.

15 Jun 2012 Grouping of 2 function Function that generates all possible groups of 2 Author: Alex Dytso Jos (10584)

This functionality is already provided by the generic matlab function NCHOOSEK. See NCHOOSE2 for a very fast implementation of nchoosek with k =2, that does the same is submission, but much faster:

tic ; A = group(1:500) ; toc ;
% Elapsed time is 11.030943 seconds.
tic ; B = nchoose2(1:500) ; toc ;
% Elapsed time is 0.014382 seconds.
isequal(A,B)
% ans = 1

This submission Group uses a nested for-loop without pre-allocation making it quite slow.

NCHOOSE2 can be found here:
http://www.mathworks.com/matlabcentral/fileexchange/20144

15 Jun 2012 Grouping of 2 function Function that generates all possible groups of 2 Author: Alex Dytso Jos (10584)

05 Jun 2012 PassWord Generatro PassWord Generator for MatLab Author: Alex Dytso Alex Dytso

I agree with all of your statements especially the one about entropy. I will submit version 2 shortly. Thank you

05 Jun 2012 PassWord Generatro PassWord Generator for MatLab Author: Alex Dytso Jan Simon

The length of the password and the number of digits, upper and lowercase letters must be specified. Special characters as !"ยง$%&/()=?*+~#-:;,.-<>|'@^ and space are not possible. This is not a typical strategy to create a password, because this reduces the entropy substantially. A simpler and more efficient approach to get a random password of n characters:
v = char([33:95, 97:27]);
p = v(ceil(rand(1,n)*length(v)));
But it is impossible to remember such passwords and it is very likely that you find them written down under the keyboard.
I prefer passwords like "65eels!NoHeels" or "I sit right beside the 5TH prime".
However, the function works, has a very lean help text, but no H1 line (see LOOKFOR). It would be more efficient to use 'ABC...' instead of ['A', 'B', 'C', ...] and to shuffle the characters of the string instead of creating an index vector at first, shuffle the index and apply it to the string finally.
The unnecessary weakness of the password is the main reason for my low voting.

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