Download presentation

Presentation is loading. Please wait.

Published byEaston Crawford Modified over 3 years ago

1
Test: CNN vs. AMM Data: Four sets of Jail Break data from ARL/Penn State Total Negative 88 Total Positive 69 Total 157 Two sets of five tests on all four data sets July 15, 2013 James P. LaRue Jadco Signals

2
y=double(y); yy=y(:,:,1); yy1=yy(1:3:end,:); yy2=yy(2:3:end,:); yy3=yy(3:3:end,:); Y1=yy1+yy2+yy3; yy1=Y1(:,1:2:end); yy2=Y1(:,1:2:end); Y2=yy1+yy2; KeepN(:,:,k)=Y2(5:32,3:end); Convert 120x60 JPEGS into 28x28

3
Examples of: NOT PRESENT Examples of: PRESENT

4
Accuracy Train with random pick 25/157 Epoch-One training cycle of 25 1.00 0.82 0.07 0.94 1.00 0.78 0.18 0.97 0 0.79 1.00 0.95 0.72 0.73 0.98 0.97 1.00 0.80 0.86 0.95 1.00 0.93 0 0.72 Not Present Present CNN AMM 1 2 3 4 5 10 Number of Epochs Mean = 0.78 0.81 0.51 0.92 Variance = 0.16 0.01 0.23 0.01

5
Time to execute 157 decisions After training CNN AMM 0.3423 0.020 0.3407 0.0171 0.3435 0.0176 0.3427 0.0176 0.3400 0.0176 0.3296 0.0167 meantime 0.3398 0.0179 1.05 3.05 4.10 2.10 2.75 4.85 3.15 2.88 6.03 4.20 2.75 6.95 5.24 2.86 8.10 10.50 2.89 13.39 1 2 3 4 5 10 Number of Epochs CNN AMM AMM+CNN Time in Minutes Train with random pick 25/157 Epoch-One training cycle of 25 Training Time

6
Accuracy Train with random pick 20/157 Epoch-One training cycle of 20 1.00 0..79 0.15 0.94 0.96 0.79 0.37 0.97 1.0 0.79 0.14 0.95 0.97 0.79 0.75 0.97 0.93 0.71 1.00 0.97 1.00 0.90 0 0.76 Not Present Present CNN AMM 1 2 3 4 5 10 Number of Epochs Mean = 0.97 0.80 0.40 0.92 Variance = 0.00 0.00 0.15 0.00

7
1The CNN has to train first. Then AMM can train. Thus, Total train time for AMM Includes CNN train time. 2 Compare total time to accuracy of CNN vs AMM. Example: from accuracy slide Across all Epochs: AMM scored 86%, CNN scored 65% 3 AMM is always consistent across Epochs. CNN is not consistent. Similar results can be shown for other tests. Note several CNN ‘all or nothing’ classifications. 4.AMM execution time recorded with single shot matrix. CNN always needs to run through all its steps, whereas multiple AMM matrices can be compressed into one matrix. 5.Note: For MNIST data set, CNN required 60 minutes to attain 80% accuracy, while AMM required 6 CNN minutes to reach 78%. 6.Conclusion: If time is not a factor, then use logic based CNN. However, if time is a factor, then use intuitive based AMM, knowing the decision will be robust. Discussion

Similar presentations

Presentation is loading. Please wait....

OK

Numerical Methods for Option Pricing

Numerical Methods for Option Pricing

© 2018 SlidePlayer.com Inc.

All rights reserved.

By using this website, you agree with our use of **cookies** to functioning of the site. More info in our Privacy Policy and Google Privacy & Terms.

Ads by Google

Ppt on nestle india ltd company Ppt online shopping system Pdf to ppt online free Best seminar ppt on robots Convert a pdf to ppt online Historical backgrounds for ppt on social media Ppt on circuit breaker switching and arc modeling Ppt on views in dbms tutorial Ppt on mobile apps Ppt on gunn diode