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Dr. Rami Khushaba

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www.rami-khushaba.com

Professional Interests:
signal processing, feature extraction and reduction

 

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13 Sep 2013 Fuzzy Entropy and Mutual Information An implementation of the theory of fuzzy entropy and fuzzy mutual information. Author: Dr. Rami Khushaba fuzzy entropy, fuzzy mutual informat... 69 11
  • 5.0
5.0 | 3 ratings
11 Feb 2013 Feature Extraction Using Multisignal Wavelet Transform Decomposition Feature extraction using the wavelet transform. Author: Dr. Rami Khushaba feature extraction, wavelet transform 67 7
  • 3.66667
3.7 | 3 ratings
03 Oct 2012 Screenshot Feature Extraction Using Multisignal Wavelet Packet Decomposition Its simply a feature extraction code using the Wavelet Packet Transform (WPT). Author: Dr. Rami Khushaba feature extraction, wavelet packet transf..., dear dr rami 104 34
  • 4.8
4.8 | 6 ratings
13 Feb 2012 Fuzzy Neighbourhood Preserving Analysis with QR-Decomposition Feature reduction (projection) using fuzzy discriminant analysis with QR-decomposition. Author: Dr. Rami Khushaba feature projection, fuzzy discriminant an... 22 1
  • 5.0
5.0 | 2 ratings
24 Jul 2011 Differential Evolution Based Channel and Feature Selection http://dx.doi.org/10.1016/j.eswa.2011.03.028 Author: Dr. Rami Khushaba differential evolutio..., feature selection 39 11
  • 5.0
5.0 | 3 ratings
Comments and Ratings by Dr. Rami View all
Updated File Comments Rating
24 Feb 2014 FilterM A faster FILTER and FILTFILT: Speedup factor 2.5 to 25 Author: Jan Simon

14 Feb 2014 Feature Extraction Using Multisignal Wavelet Transform Decomposition Feature extraction using the wavelet transform. Author: Dr. Rami Khushaba

Dear Hamed abdulaziz & Prabhakar

Thank you for your inquiries. I work mainly in signal feature extraction, rather than image feature extraction. My Suggestions for you could be:
1- Reshape each image into vector and apply this code on each vector.
2- OR, use the 2D wavelet decomposition commands (more suitable for images) and extract your features from each node in the same way am doing here. Note with the 2D version, you will have a small image at each node and you can use something like moment invariants to get the features from each image. Look here (http://www.mathworks.com.au/matlabcentral/fileexchange/33975-the-seven-invariant-moments)

Thanks

06 Jan 2014 Fuzzy Entropy and Mutual Information An implementation of the theory of fuzzy entropy and fuzzy mutual information. Author: Dr. Rami Khushaba

Hi ZoidBerg

Just make sure that your class label, this is the last column in data, is actually organized as 1 2 3 4 etc..., i.e., the label haves consecutive numbering and in that case you can ignore or comment the grp2idx function.

Rami

17 Nov 2013 Feature Extraction Using Multisignal Wavelet Packet Decomposition Its simply a feature extraction code using the Wavelet Packet Transform (WPT). Author: Dr. Rami Khushaba

Dear Deepak

Thank you for your inquiry, you are actually right about SF. However, please note the comment in the code, that is you can use the sampling frequency to determine the actual number of decomposition levels J, I remember having a comment in the code about that in the same line where I defined J=7 (comment says you can use J=(log(SF/2)/log(2))-1;). I fixed the decomposition levels in the code sample you mentioned to make it easy for new users to understand it, but you can change that by using the commented equation.

Rami

14 Sep 2013 Fuzzy Entropy and Mutual Information An implementation of the theory of fuzzy entropy and fuzzy mutual information. Author: Dr. Rami Khushaba

Hello

For those interested in mutual information based feature selection, you can use this code with the well-known MRMR feature selection algorithm from: http://www.mathworks.com.au/matlabcentral/fileexchange/14916-minimum-redundancy-maximum-relevance-feature-selection

You will have to adjust the fuzzification parameter m to reflect better performance. You will also have to modify the original function by Hanchuan Peng into the following:

==================================

function [fea] = mrmr_mid_d(d, f, K,I_Cx,I_xx)
% MID scheme according to MRMR
% Original By Hanchuan Peng
% April 16, 2003
% Modification By Rami Khushaba
% 13/09/2013

bdisp=0;
nd = size(d,2);
nc = size(d,1);
t1=cputime;
t = I_Cx;
[tmp, idxs] = sort(t,'descend');
fea_base = idxs(1:K);
fea(1) = idxs(1);
KMAX = min(1000,nd); %500
idxleft = idxs(2:KMAX);
k=1;
if bdisp==1,
fprintf('k=1 cost_time=(N/A) cur_fea=%d #left_cand=%d\n', ...
fea(k), length(idxleft));
end;

for k=2:K,
t1=cputime;
ncand = length(idxleft);
curlastfea = length(fea);
for i=1:ncand,
t_mi(i) = I_Cx(idxleft(i));
mi_array(idxleft(i),curlastfea) = I_xx(fea(curlastfea), idxleft(i));
c_mi(i) = mean(mi_array(idxleft(i), :));
end;
[tmp, fea(k)] = max(t_mi(1:ncand) - c_mi(1:ncand));
tmpidx = fea(k); fea(k) = idxleft(tmpidx); idxleft(tmpidx) = [];
if bdisp==1,
fprintf('k=%d cost_time=%5.4f cur_fea=%d #left_cand=%d\n', ...
k, cputime-t1, fea(k), length(idxleft));
end;
end;
return;

Post any question related to fuzzy MI and I will try to reply as soon as possible.

Thanks
Rami

Comments and Ratings on Dr. Rami's Files View all
Updated File Comment by Comments Rating
07 Jun 2014 Fuzzy Entropy and Mutual Information An implementation of the theory of fuzzy entropy and fuzzy mutual information. Author: Dr. Rami Khushaba md

hello

thank you for sharing it! i have a question i tried your fuzzy code with a signal with gaussian nose and always return de same value

i'm wondering if is possible to read “Novel Feature Extraction Method based on Fuzzy Entropy and Wavelet Packet Transform for Myoelectric Control” for understand how to enter the input signal ..i was looking in internet but i cant find it!

14 Feb 2014 Feature Extraction Using Multisignal Wavelet Transform Decomposition Feature extraction using the wavelet transform. Author: Dr. Rami Khushaba Khushaba, Dr. Rami

Dear Hamed abdulaziz & Prabhakar

Thank you for your inquiries. I work mainly in signal feature extraction, rather than image feature extraction. My Suggestions for you could be:
1- Reshape each image into vector and apply this code on each vector.
2- OR, use the 2D wavelet decomposition commands (more suitable for images) and extract your features from each node in the same way am doing here. Note with the 2D version, you will have a small image at each node and you can use something like moment invariants to get the features from each image. Look here (http://www.mathworks.com.au/matlabcentral/fileexchange/33975-the-seven-invariant-moments)

Thanks

14 Feb 2014 Feature Extraction Using Multisignal Wavelet Transform Decomposition Feature extraction using the wavelet transform. Author: Dr. Rami Khushaba abdulaziz, hamed

Dear Dr. Rami.Khushaba,

please How to use this method to extract the features from image.

I'll wait for your answer impatiently.

06 Jan 2014 Fuzzy Entropy and Mutual Information An implementation of the theory of fuzzy entropy and fuzzy mutual information. Author: Dr. Rami Khushaba Khushaba, Dr. Rami

Hi ZoidBerg

Just make sure that your class label, this is the last column in data, is actually organized as 1 2 3 4 etc..., i.e., the label haves consecutive numbering and in that case you can ignore or comment the grp2idx function.

Rami

14 Dec 2013 Feature Extraction Using Multisignal Wavelet Transform Decomposition Feature extraction using the wavelet transform. Author: Dr. Rami Khushaba Prabhakar

Dear Dr. Khushaba,

How to use this method to extract the features for image

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