Sensors and Filtering

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Unformatted text preview: Click to edit Master subtitle style 10/15/10 Sensors and Filtering 10/15/10 S&D - 1 Sensors and Data Acquisition Measured signal = Signal + Noise Knowledge about the structure of noise can be used to design filters for noise removal. Simple (but effective) filters can often be derived from first and second order statistics computed from signal samples. 10/15/10 S&D - 2 Experiment: Write a program to drive a cart with a light sensor across a carpet with uniform color. What does the signal look like? Well show you how to log data captured from the brick in a few slides. This data can then be copied into an Excel spreadsheet with a couple of mouse clicks. 10/15/10 S&D - 3 Sensors and Data Acquisition, cont. Lets look at the data acquired by the Cart in detail. Excel can do plots as well as provide Descriptive Statistics C o lu m n 1 M e a n 1 9 7 . 9 2 7 8 3 5 S t a n d a r d E r r o r 2 . 6 6 5 1 3 2 4 8 M e d ia n 1 9 6 M o d e 2 2 1 S t a n d a r d D e v ia t i 2 6 . 2 4 8 5 1 0 8 S a m p le V a r ia n c e 6 8 8 . 9 8 4 3 2 1 K u r t o s is - 0 . 5 1 0 4 2 8 5 5 S k e w n e s s 0 . 2 3 8 0 2 6 1 R a n g e 1 1 8 M in im u m 1 4 4 M a x im u m 2 6 2 S u m 1 9 1 9 9 C o u n t 9 7 10/15/10 S&D - 3 Basic Statistics and their Usage The formulae for the...
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