Date  File  Comment by  Comment  Rating 

20 Oct 2014  Random Walk Demonstrates concept of a random walk  mostafa khalili  
19 Sep 2014  LMMSE Equalizer Implementation of LMMSE (linear minimum mean square error) Equalizer used to combat ISI  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  S R M Universiry  Please send me the lmmse program. 

14 May 2014  Extended Kalman Filter Tracking Object in 3D Using Kalman filter to track object in 3D. Comparing Extended Kalman filter to its linear version.  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 3D Using Kalman filter to track object in 3D. Comparing Extended Kalman filter to its linear version.  Ahsan  The value of Z is unused from argument in proccesANDobserve and Jacobian function. 

14 May 2014  Extended Kalman Filter Tracking Object in 3D Using Kalman filter to track object in 3D. Comparing Extended Kalman filter to its linear version.  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 3D Using Kalman filter to track object in 3D. Comparing Extended Kalman filter to its linear version.  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 3D Using Kalman filter to track object in 3D. Comparing Extended Kalman filter to its linear version.  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  fibrlink,com lu  
05 Feb 2014  Zero Forcing Equalizer Simulation This code is demonstrates implementation of Zero Forcing Equalizer in a communication channel  Liping Wang  
01 Feb 2014  Scalar Kalman Filter This code serves as a tutorial for implementation of Scalar Kalman Filter  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  jeffin  good 

30 Sep 2013  Extended Kalman Filter Tracking Object in 3D Using Kalman filter to track object in 3D. Comparing Extended Kalman filter to its linear version.  yatie SUAIB  ok,thank you very much 

26 Sep 2013  Extended Kalman Filter Tracking Object in 3D Using Kalman filter to track object in 3D. Comparing Extended Kalman filter to its linear version.  Alex Dytso  Yes, here is the document this is based on


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


31 Mar 2013  Extended Kalman Filter Tracking Object in 3D Using Kalman filter to track object in 3D. Comparing Extended Kalman filter to its linear version.  Alex Dytso  In order to convert to 2D 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 3D Using Kalman filter to track object in 3D. Comparing Extended Kalman filter to its linear version.  Atef  please how apply this code for 2D ? 

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

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

30 Dec 2012  Extended Kalman Filter Tracking Object in 3D Using Kalman filter to track object in 3D. Comparing Extended Kalman filter to its linear version.  W. Chong  
15 Jun 2012  Grouping of 2 function Function that generates all possible groups of 2  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  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 ;
This submission Group uses a nested forloop without preallocation making it quite slow. NCHOOSE2 can be found here:


15 Jun 2012  Grouping of 2 function Function that generates all possible groups of 2  Jos (10584)  
05 Jun 2012  PassWord Generatro PassWord Generator for MatLab  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  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:

