njit-etd2003-081 - New Jersey Institute of Technology
njit-etd2003-081 - New Jersey Institute of Technology njit-etd2003-081 - New Jersey Institute of Technology
295 Hotelling's T2 (Fourth Output) 15. The last output of the princomp function, t2, is Hotelling's T2, a statistical measure of the multivariate distance of each observation from the center of the data set. This is an analytical way to find the most extreme points in the data. >> [st2, index] = sort(t2); % Sort in ascending order. >> st2 = flipud(st2); % Values in descending order. >> index = flipud(index); % Indices in descending order. >> extreme = index(1) extreme = 10 >> names(extreme,:) ans = ecc It is not surprising that the ratings for COPD subject `ecc' is the furthest from the average COPD group.
296 B.2.7 Cluster Analysis Program This program is a MATLAB m-file. Upon starting MATLAB, type whitebg for a white graphic background. 1. The data needed is the data set formed from 15 HRV parameters as the results of PCA on real COPD/Normal data and cross-spectral analysis. The data set is saved as an ASCII file. In order to load it into MATLAB. Type: load Agul.asc; Note: Agul is the filename. If you now type whos, the file should show up as the variable Agul. 2. Run the program using the general format: [RITrue,RISelf,EstIndex]=DoClustering(Algorithm,Data,k,TrueID,Repetitions) [algo, self, 2]=DoClustering(kmeans, Agu1,5„2) Here, data is Agul, k=5 clusters and run 2 repetitions. 3. The program will run and output a plot with five separate clusters as asked in the above command.
- Page 273 and 274: 244 A.3 Figure Out Your Target Hear
- Page 275 and 276: APPENDIX B ANALYSIS PROGRAM LISTING
- Page 277 and 278: 248 4) Click on file, close to exit
- Page 279 and 280: 250 • TN 11
- Page 281 and 282: 252 B.1.2 Partial Coherence Between
- Page 283 and 284: 254
- Page 285 and 286: 256 Block Diagram !rime of record K
- Page 287 and 288: 258
- Page 289 and 290: 260 B.2.2 Time — Frequency Analys
- Page 291 and 292: 262 This program provides the STFT
- Page 293 and 294: 264 G(:j+1)=G(:,j+1)/(2*sum(G(:j+1)
- Page 295 and 296: 266 T=(length(Signa)/sample)/(Times
- Page 297 and 298: 268 subplot(3, 1,3), plot(T,E); xla
- Page 299 and 300: 270 4. The program creates five out
- Page 301 and 302: 272 B.2.3.4 Program to Generate Sym
- Page 303 and 304: 274 ylabel('frequency'); title('Ins
- Page 305 and 306: 276 The program will run and output
- Page 307 and 308: 278 axis([0 1 0 2]); grid on; xlabe
- Page 309 and 310: 280 vagal=sum(TFDs(HFC,1:k)); symto
- Page 311 and 312: 282 plot(J,symtopar); %plot(A,symto
- Page 313 and 314: 284 4. Remove the constant levels a
- Page 315 and 316: 286 Make sure the agreement is quit
- Page 317 and 318: 288 B.2.6 Principal Components Anal
- Page 319 and 320: 290 Columns 12 through 15 'LF_pcoh_
- Page 321 and 322: 292 I= 1.0000 -0.0000 -0.0000 -0.00
- Page 323: 294 variances = 3.4083 1.2140 1.141
- Page 327 and 328: 298 end [R,C]=size(Data); if length
- Page 329 and 330: 300 B.2.8 Cross-correlation Program
- Page 331 and 332: 302 C.3 Partial coherence of HR and
- Page 333 and 334: 304 [13] Madwed, J., and R. Cohen.
- Page 335 and 336: 306 [41] Mallat, S. G., "A Theory f
- Page 337: [70] Tazebay, M.V., R.T. Saliba and
296<br />
B.2.7 Cluster Analysis Program<br />
This program is a MATLAB m-file. Upon starting MATLAB, type whitebg for a white<br />
graphic background.<br />
1. The data needed is the data set formed from 15 HRV parameters as the results <strong>of</strong><br />
PCA on real COPD/Normal data and cross-spectral analysis. The data set is saved as an<br />
ASCII file. In order to load it into MATLAB. Type:<br />
load Agul.asc; Note: Agul is the filename.<br />
If you now type whos, the file should show up as the variable Agul.<br />
2. Run the program using the general format:<br />
[RITrue,RISelf,EstIndex]=DoClustering(Algorithm,Data,k,TrueID,Repetitions)<br />
[algo, self, 2]=DoClustering(kmeans, Agu1,5„2)<br />
Here, data is Agul, k=5 clusters and run 2 repetitions.<br />
3. The program will run and output a plot with five separate clusters as asked in the<br />
above command.
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