Rank: 6 based on 3423 downloads (last 30 days) and 66 files submitted
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Yi Cao

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Cranfield University
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52.073917, -0.628756

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http://www.cranfield.ac.uk/about/people-and-resources/academic-profiles/soe-ac-profile/dr-yi-y-cao.html

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Files Posted by Yi View all
Updated   File Tags Downloads
(last 30 days)
Comments Rating
03 Apr 2014 Screenshot Pareto Set find the pareto set from n points with k objectives Author: Yi Cao optimization, multiobjective optimi..., pareto set, dorini 40 10
  • 3.66667
3.7 | 3 ratings
06 Feb 2014 Conjugate Gradient Method Conjugate Gradient Method to solve a system of linear equations Author: Yi Cao mathematics, linear algebra, linear equation, optimization 69 3
  • 5.0
5.0 | 2 ratings
12 Aug 2013 Screenshot Bivariant Kernel Density Estimation (V2.1) A tool for bivariant pdf, cdf and icdf estimation using Gaussian kernel function. Author: Yi Cao statistics, probability, bivariant gaussian ke..., kernel density estima..., bivariant pdf, cdf 76 6
  • 4.57143
4.6 | 7 ratings
11 Apr 2013 LAPJV - Jonker-Volgenant Algorithm for Linear Assignment Problem V3.0 A Matlab implementation of the Jonker-Volgenant algorithm solving LAPs. Author: Yi Cao linear assignment pro..., linear assignment pro..., optimization, hungarian algorithm, munkres algorithm 54 44
  • 5.0
5.0 | 15 ratings
19 Feb 2013 Screenshot Improvd downward branch and bound algorithm for regression variable selection Improved downward branch and bound to select the best subset for least squares regression problems. Author: Yi Cao optimization 24 0
Comments and Ratings by Yi View all
Updated File Comments Rating
19 Apr 2014 Pareto Front Two efficient algorithms to find Pareto Front Author: Yi Cao

Adarsh,

If you delete the first line, you will get it working.

Good luck
Yi

01 Jan 2013 Fuel Cell Model Fuel Cell Model is presented Author: Siva Malla

The model has several "Bad Link", hence cannot run.

05 Sep 2012 Bidirectional Branch and Bound for Average Loss Minimization Two algorithms for selection of controlled variables using the average loss as the criterion. Author: Yi Cao

Hi Steffen,

If Y is rank difficient, the original formular has to change because it was derived based on the assuption YY^T is not signular. As you said, this only possiblelly happens when measurement errors are ignored. In other words, we can always add very small measurement errors to avoid such singularity. You can always assume Wn = eI with a sufficiently small e to make the code works.

Hope this helps.

Yi

06 May 2012 LAPJV - Jonker-Volgenant Algorithm for Linear Assignment Problem V3.0 A Matlab implementation of the Jonker-Volgenant algorithm solving LAPs. Author: Yi Cao

Thank you Dmitri, the bug has been fixed now.

Yi

21 Sep 2011 Hungarian Algorithm for Linear Assignment Problems (V2.3) An extremely fast implementation of the Hungarian algorithm on a native Matlab code. Author: Yi Cao

Well, I can see what you try to do is to increase the cost of selected assignment then to find next best assignment. However, you made a wrong change. The assignment results in dicated row 1 assigned with colume 3, but you miss understood as column 1 assigned with row 3. Wish this helps.

Comments and Ratings on Yi's Files View all
Updated File Comment by Comments Rating
22 Jul 2014 Learning PID Tuning III: Performance Index Optimization A tool and tutorial to perform optimal PID tuning Author: Yi Cao Maria

Hello,
I tried using the optimPID function for a second-order system but I get the following error message: 'Error using fminusub (line 17)
Objective function is undefined at initial point. Fminunc cannot
continue.'
Any help would be greatly appreciated.
Thank you.

21 Jul 2014 Learning the Kalman Filter in Simulink v2.1 A Simulink model to learn the Kalman filter for Gassian processes. Author: Yi Cao Guanlin

thanks a lot!

26 Jun 2014 Learning the Unscented Kalman Filter An implementation of Unscented Kalman Filter for nonlinear state estimation. Author: Yi Cao Matthew

I found that for my system, the covariance matrix was growing like crazy (P_k~10^8*P_k-1) and was getting complex.

Try adjusting the alpha parameter. 10e-3 was way too small for my system, and 0.1 was the bare minimum that I could avoid the covariance issues. 0.15 seemed to work best.
in general, alpha is recommended to be between 10e-3 and 1.

29 May 2014 Learning the Unscented Kalman Filter An implementation of Unscented Kalman Filter for nonlinear state estimation. Author: Yi Cao Hien

Hi everybody!
I really have not understood this code yet. In my case, I also study on EKF for GPS data that I want to apply EKF to due with noise and missing data in GPS data. I have one GPS data columm with more than 2000 of length. Who could show me how to do it?
Thank you so much for your kinds

29 May 2014 Learning the Extended Kalman Filter An implementation of Extended Kalman Filter for nonlinear state estimation. Author: Yi Cao Hien

Hi everybody!
I really have not understood this code yet. In my case, I also study on EKF for GPS data that I want to apply EKF to due with noise and missing data in GPS data. I have one GPS data columm with more than 2000 of length. Who could show me how to do it?
Thank you so much for your kinds

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