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Adaptive Noise Cancellation: A Panacea M.Evans, R. Adhikari.

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Presentation on theme: "Adaptive Noise Cancellation: A Panacea M.Evans, R. Adhikari."— Presentation transcript:

1 Adaptive Noise Cancellation: A Panacea M.Evans, R. Adhikari

2 The Concept 5000 Channels 1 GW Channel Signal = DARM - noise

3 Wiener Filter Input Signal (PEM) Covariance Matrix Norbert Wiener, MIT Block Toeplitz Cross Correlation Matrix

4 Wiener Filter Sim H1 & L1 DARM (S5) All Guralp & STS2 Vault not used Requires ~9 GB RAM Levinson-Durbin H1 L1 x10 x7

5 Adaptive Filtering / Neural Network Keenan Pepper Elena Gasparri LMS Algorithm (1st chapter of textbooks)

6 ATNF

7 Filtered-X LMS Edwards, Thesis (declassified) Naval Research Postgraduate School

8 Applications Seismic Noise (0 - 40 Hz) Upconversion Lock Acquisition Bilinear (Crab shoulder) Acoustic Noise (50-900 Hz) Magnetic (power lines) H1/H2 correlation MICH/PRC/SRC

9 From LMS to Filtered-X LMS FIR Adapt Noise Witness Noisy Signal Cleaner Signal

10 From LMS to Filtered-X Injecting into a high gain servo loop FIR Adapt Noise Witness Total Control Signal Servo Control Signal G

11 From LMS to Filtered-X Separated Actuators Special case of “Filtered X- LMS” FIR Adapt Noise Witness Total Control Signal Servo Control Signal A1 G A2 C

12 At the 40m Test on input mode- cleaner FIR Adapt Seismic Sensors MC Length MC_L MC2 G MC1 C

13 At the 40m

14

15 And more !


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