Changes between Version 40 and Version 41 of Old/Dailyupdates

Timestamp:

Jun 29, 2007, 2:14:56 PM (17 years ago)

Author:

aniket

Comment:

—

Old/Dailyupdates

@@ -35 +35 @@
 Ivan suggested a using a statistical method to fit data so that our programs will function more efficeintly.  The following week is going to be spent working on that.
 
+== 6/28/07 - Day 19 ==
 
+Today was an educational day. We have been reviewing our statistics and reading up on signal processing. We ran an experiment and collected some data to use to work out our statistical algorithms. The experiment was as followed: We set up an access point out in the hall way and had a robot drive strait passed it, never stopping but collecting signal strength and position data the whole way through. Two trials were run - in one the source was right at the beginning of the robot's motion, and at another the source was midway between the robots start and end points.
+
+We found an interesting fact in MadWifi's documentation - the scale we use to measure signal strength (dbm) was specifically chosen to be linear with distance. We went ahead and performed a least square regression and fit a line  to the data from the first test. The line fit well but something is wrong with my code that calculates RMS value - I will debug that.
+
+Next, looking at the second test, we found a very distinct U shaped pattern in signal strength with distance. We estimated the location of the minimum with our eyes and fit two LSLs (least square regressions). Rather than eyeball it, I thought we should find the code that finds the location along the distance axis which calculates the lowest over all square regressions (summing the regressions from the two lines). It takes a large amount of computer power (approx 15sec) to compute the total regression for every possible location, but in the end we see another distinct U-shaped curve with a minimum right about at the location of the access point.
+
+We downloaded the packages scipy, numpy, and ipython today. I believe they will prove very useful. Up until now, the numerical analysis has been performed in Octave or Matlab, but if we can port it over to python we can write robot scripts which perform numeric analysis in real time and respond to it.
+
+I am currently reading about the Fourier Transform in attempt to understand filters. I understande scipy contains some built in functions for filters and fft. Hopefully before long we'll at least be able to implement a filter, if not design an appropriate one of our own.