Search Comments and Ratings

View All Comments and Ratings by:
Most Recent
Rank

Comments and Ratings

E-mail this View
			1 - 50 of 278
Date	File	Comment by	Comment	Rating
21 Nov 2009	Configurable Simulink Model for DC-DC Converters with PWM PI Control A Simulink model configurable to buck, boost and buck-boost DC-DC converters with PWM PI control Author: Yi Cao	caizhi, zhang	Hi,Dr. Cao Thanks for your excellent work! I don't understand the PWMPID controler, Could you tell me why did you design the controler like that? Thanks!
17 Nov 2009	Bidirectional Branch and Bound Minimum Singular Value Solver (V2) A branch and bound solver to find the largest minimum singular values among all submatrices. Author: Yi Cao	Hoeser, Stefan
16 Nov 2009	Hypervolume Indicator A tool to estimate the hypervolume indicator Author: Yi Cao	Matteo	Thank you, it's perfect!
02 Nov 2009	Hungarian Algorithm for Linear Assignment Problems (V2.1) An extremely fast implementation of the Hungarian algorithm on a native Matlab code. Author: Yi Cao	James
22 Oct 2009	Bivariant Gaussian Kernel Density Estimation A too for bivariant probability density estimation using Gaussian kernel function. Author: Yi Cao	Jandreau, Tyler
21 Oct 2009	Pareto Front Two efficient algorithms to find Pareto Front Author: Yi Cao	Buzatu, Pompilia	Can anyone explain to me how to use these files? :-/ Thank you!
27 Aug 2009	Kernel Smoothing Regression A non-parametrical regression (smoothing) tool using Gaussian kernel. Author: Yi Cao	, cf	It works very well and friendly.
20 Aug 2009	Pareto Front Two efficient algorithms to find Pareto Front Author: Yi Cao	Cao, Yi	Yes, you can. For a higher dimension, you have to provide much more data points. HTH Yi
19 Aug 2009	mvaverage moving average through filter Author: Yi Cao	Ryan	Fast and simple code. Works as advertised.
12 Aug 2009	Pareto Front Two efficient algorithms to find Pareto Front Author: Yi Cao	Subramanian, BASKAR	Hi, Can we use this code for more than two objectives? We are getting the scattered front when using more than two objectives.
11 Aug 2009	Learning the Extended Kalman Filter An implementation of Extended Kalman Filter for nonlinear state estimation. Author: Yi Cao	icar, iasri	hi yi, would like to know if its appropriate to use EKF for forecasting of agricultural yields like fish ,rice etc. i am planning to use EXPAR with EKF for the problem stated above and would you kindly be able to give some of your ideas regarding the same.thankyou, with regards bishal.
20 Jul 2009	Learning the Extended Kalman Filter An implementation of Extended Kalman Filter for nonlinear state estimation. Author: Yi Cao	Rathinasamy, maheswaran
08 Jul 2009	Efficient K-Means Clustering using JIT A simple but fast tool for K-means clustering Author: Yi Cao	Kraft, Edgar	The code is very nice and well documented. In some cases, however, the clusters are not properly identified if no initial centroid vectors are provided. This could be improved by automatically trying a small number of different random initial guesses and chosing the configuration which yields the smallest sum of distance between points and centroids.
23 Jun 2009	Learning the Unscented Kalman Filter An implementation of Unscented Kalman Filter for nonlinear state estimation. Author: Yi Cao	Schenkel, Peter	ok for some reasion my previous posting got lost , so once again : I am using UKF to estimate distances from radio signal strength. Eventhough the RSSI error (measurement equation) is gauss distributed UKF performs very poorly and I cannot understand why as it seems the perfect choice for this kind of problem. I set the measurment nois to the std I got from the training data. My system equations are f=@(x)[abs(x(1)+x(2));abs(x(3)-x(1));x(1)] ; h=@(x)[-log10(x(1))10pl-A]; for f : x1: new distance = old distance + velocity x2: velocity = difference(old distance, new distance) x3: old distance h is simply a given transformation from distance to radio singal strength I cannot find any reason for the poor performance as it should be the best filter for this kind of application. Am I missing some important issues ?
23 Jun 2009	Learning the Unscented Kalman Filter An implementation of Unscented Kalman Filter for nonlinear state estimation. Author: Yi Cao	Schenkel, Peter	sorry...ekf should be ukf in the previous posting
21 Jun 2009	Learning the Unscented Kalman Filter An implementation of Unscented Kalman Filter for nonlinear state estimation. Author: Yi Cao	Cao, Yi	Peter, This means the iteration of ukf is unstable. You have to adjust P, Q, etc to make it stable. Yi
20 Jun 2009	Learning the Unscented Kalman Filter An implementation of Unscented Kalman Filter for nonlinear state estimation. Author: Yi Cao	Schenkel, Peter	Hi Yi Cao, First of all, thanks for your contribution here. I do have a question though, I do get for some parameter combinations a complex covariance matrix, the parameters look like this : z = -78 c = 1.7321e-004 P = 1.2500 + 0.0000i 0.0000 - 0.0000i 0.0000 - 0.0000i 0.0000 + 0.0000i 0.4438 + 0.0000i 0.0000 + 0.0000i 0.0000 + 0.0000i 0.0000 - 0.0000i 1.2500 + 0.0000i x = 0.5807 - 0.0000i -5.5018 + 3.7078i 0.7954 - 0.0000i Then I get this error : ??? Error using ==> chol Matrix must be positive definite with real diagonal. I assume that this is due to the complex covariance matrix. I have no idea how this matrix can become complex as in my oppinion the only way it can become complex is if c would be negative which it isn't here... Additionally, I would like to measure distances using radio signal strength, therefore I have actually the distances from RSSI values and additional velocity from the last step to the current step, is it possible to process these information with this implementation as well ? Thanks for any help! Best Peter
08 Jun 2009	Learning the Extended Kalman Filter An implementation of Extended Kalman Filter for nonlinear state estimation. Author: Yi Cao	tim	i wrote a very simple compound pendulum code, and some how this ekf algorithm does not work for that. only change that i had to do to that example file was change the states to 2 and rest f=@(x)[x(2);-(g/l)*sin(x(1))]; this should give me sinusoidal waveform but it does not. can you point out to me what could be wrong.
06 Jun 2009	Learning the Unscented Kalman Filter An implementation of Unscented Kalman Filter for nonlinear state estimation. Author: Yi Cao	Cao, Yi	Right. However, K=P12inv(P2). Hence, KP2 = P12. This leads to KP2K' = P12K'. Therefore, P=P1-P12K'. HTH Yi
05 Jun 2009	Learning the Unscented Kalman Filter An implementation of Unscented Kalman Filter for nonlinear state estimation. Author: Yi Cao	Robers, Erik	I think the covariance updat should be: P=P1-KP2K' Erik
27 May 2009	Multivariable Subspace Identification: MOESP A tool for subspace identification using the MOESP algorithm. Author: Yi Cao	Bizkevelci, Erdal
26 May 2009	Learning the Extended Kalman Filter An implementation of Extended Kalman Filter for nonlinear state estimation. Author: Yi Cao	Heights, tim	if in EKF i have to add state noise compensation, any good example or guidance here. how can i add to the example given by Yi Cao. secondly, any one who could also recommend some book about it.
23 May 2009	Learning the Extended Kalman Filter An implementation of Extended Kalman Filter for nonlinear state estimation. Author: Yi Cao	Chao
13 May 2009	Configurable Simulink Model for DC-DC Converters with PWM PI Control A Simulink model configurable to buck, boost and buck-boost DC-DC converters with PWM PI control Author: Yi Cao	colhn, colhano
28 Apr 2009	Learning the Extended Kalman Filter An implementation of Extended Kalman Filter for nonlinear state estimation. Author: Yi Cao	Cao, Yi	For continuous-time EKF, please look at http://www.mathworks.com/matlabcentral/fileexchange/18485
28 Apr 2009	Learning the Extended Kalman Filter An implementation of Extended Kalman Filter for nonlinear state estimation. Author: Yi Cao	Hippalgaonkar, Rohit	Hi I am looking for an example where the EKF is applied to a continuous-time non-linear system with non-zero inputs (say measurements are taken at regular time samples through a non-linear (even linear would do) measurement process. I have looked around for this kind of example in the standard texts but haven't found any. Also a good source showing the implementation of the EKF wherein we linearize about a single operating point (as against linearizing about the predicted state every time) would be really helpful! Thanks in advance! Rohit
28 Apr 2009	Unconstrained Optimization using the Extended Kalman Filter A function using the extended Kalman filter to perform unconstrained nonlinear optimization Author: Yi Cao	Hippalgaonkar, Rohit	Hi I am looking for an example where the EKF is applied to a continuous-time non-linear system with non-zero inputs (say measurements are taken at regular time samples through a non-linear (even linear would do) measurement process. I have looked around for this kind of example in the standard texts but haven't found any. Also a good source showing the implementation of the EKF wherein we linearize about a single operating point (as against linearizing about the predicted state every time) would be really helpful! Thanks in advance! Rohit
20 Apr 2009	Learning the Unscented Kalman Filter An implementation of Unscented Kalman Filter for nonlinear state estimation. Author: Yi Cao	Cao, Yi	It seems that your model is not stable. You may wish to adjust P, Q and R matrices to see if this helps. Yi
20 Apr 2009	Learning the Unscented Kalman Filter An implementation of Unscented Kalman Filter for nonlinear state estimation. Author: Yi Cao	Chawah, Dapat	hello Dr.Yi This code is working good for N<=150 but when N exceeds this limit, a nonsense happens Is there any improvement to the code considering this error?
20 Apr 2009	Learning the Extended Kalman Filter An implementation of Extended Kalman Filter for nonlinear state estimation. Author: Yi Cao	Chawah, Dapat	Sorry, this comment is meant to be in the unscented kalman filter file discussion
20 Apr 2009	Learning the Extended Kalman Filter An implementation of Extended Kalman Filter for nonlinear state estimation. Author: Yi Cao	Chawah, Dapat	This code is working good for N<=150 but when N exceeds this limit, a nonsense happens Is there any improvement to the code considering this error?
06 Apr 2009	Complex step Jacobian Calculate Jacobian using complex step differentiation Author: Yi Cao	Cao, Yi	Angshul, eps is the minimal distinguishable vnumer for a particular precision system. For double precision, eps = 2^(-52) and for single precision, eps = 2^(-23). Use "help eps" to find more details. The complex step differentiation approach can use the minimum step size to get the maximum accuracy. Hence eps is the best step the algorithm can use. HTH. Yi
06 Apr 2009	Complex step Jacobian Calculate Jacobian using complex step differentiation Author: Yi Cao	Majumdar, Angshul	the step size 'eps' is not specified? Do U suggest a value?
06 Apr 2009	Bidirectional Branch and Bound Solvers for Worst Case Loss Minimization Two branch and bound solvers using worst case loss criterion to select controlled variables. Author: Yi Cao	Cao, Yi	Mohammad, If you are a real user who is concerned about this issue, please drop me an email. I will clarify this to you. Yi
05 Apr 2009	cholhilb Cholesky factorization of the Hilbert matrix of order n Author: Yi Cao	Poor, V.
05 Apr 2009	Peg Solitaire Contest Solver An upgraded solver for the peg solitaire contest Author: Yi Cao	Poor, V.
05 Apr 2009	recursive solver to peg solitaire contest a solver to push the 3-minute limit Author: Yi Cao	Poor, V.
05 Apr 2009	mvaverage moving average through filter Author: Yi Cao	Poor, V.
05 Apr 2009	fminconSym A wrap of fmincon to get gradient Author: Yi Cao	Poor, V.
05 Apr 2009	lsqnonlinSym A wrap of lsqnonlin to get Jacobian Author: Yi Cao	Poor, V.
05 Apr 2009	Simulink Library: Performance Index A small simulink library to provide performance index measurements. Author: Yi Cao	Poor, V.
05 Apr 2009	UK Postcode to Lat/Long for GPS A small tool to convert a UK postcode to Lat/Long degrees for GPS Author: Yi Cao	Poor, V.
05 Apr 2009	lsqnonlinCSD A wrap of lsqnonlin using complex step differentiation to get Jacobian Author: Yi Cao	Poor, V.
05 Apr 2009	fminconCSD A wrap of fmincon using complex step differentiation to calculate gradient Author: Yi Cao	Poor, V.
05 Apr 2009	Complex step Hessian Calculate Hessian using complex step differentiation Author: Yi Cao	Poor, V.
05 Apr 2009	Complex step Jacobian Calculate Jacobian using complex step differentiation Author: Yi Cao	Poor, V.
05 Apr 2009	Learning the Extended Kalman Filter An implementation of Extended Kalman Filter for nonlinear state estimation. Author: Yi Cao	Poor, V.
05 Apr 2009	Learning the Unscented Kalman Filter An implementation of Unscented Kalman Filter for nonlinear state estimation. Author: Yi Cao	Poor, V.
05 Apr 2009	Wakimapia A tool to locate the Wakimapia to specified latitude and longitude degrees Author: Yi Cao	Poor, V.
05 Apr 2009	Learning the Kalman Filter in Simulink A Simulink model to learn the Kalman filter and Gassian processes. Author: Yi Cao	Poor, V.
1 - 50 of 278
E-mail this View

MATLAB Central Terms of Use

NOTICE: Any content you submit to MATLAB Central, including personal information, is not subject to the protections which may be afforded information collected under other sections of The MathWorks, Inc. Web site. You are entirely responsible for all content that you upload, post, e-mail, transmit or otherwise make available via MATLAB Central. The MathWorks does not control the content posted by visitors to MATLAB Central and, does not guarantee the accuracy, integrity, or quality of such content. Under no circumstances will The MathWorks be liable in any way for any content not authored by The MathWorks, or any loss or damage of any kind incurred as a result of the use of any content posted, e-mailed, transmitted or otherwise made available via MATLAB Central. Read the complete Terms prior to use.