Recurrence quantitative analysis

on Monday, October 30th, 2017 11:43 | by

This is an example of a recurrence plot analysis. In the first graph is shown in single point in time in the optimal embedding dimension and the distance to the other points. For the recurrence plot analysis it is needed to put a threshold to make it binary. This is the second graph. From this second graph one can count many parameters like determinism, laminarity and so on. From what I see, the plots from the Strokelitude as well as Bjoern´s flight simulator in Maye et al 2007 show similar pattern (kind of crosses with vertical and horizontal lines).

 

 

This is a measure of the Recurrence Quantitative Analysis of different groups. Recurrence threshold is a tricky and to some extent subjective measure, so this is why I tried two different ones.

DET: recurrence points that form a diagonal line of minimal length, the more diagonal, the more deterministic.

LMAX: Max diagonal line length or divergence. Sometimes considered as an estimator of max. Lyapunov exponent

ENT: Shannon entropy reflects the complexity of the system

TND: info about stationarity (trend)

LAM: Laminarity is related to laminar phases in the system (intermittency). It is tallied as vertical lines over a threshold.

TT: Trapping time, measuring the average length of vertical lines. Related to laminarity.

 

Automat

 

One stripe

Openloop

Uniform

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DMSO as a solvent

on Friday, July 21st, 2017 11:48 | by

on Friday, July 14th, 2017 3:26 | by

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on Saturday, July 8th, 2017 1:05 | by

 

 

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Effect of Diazepam Concentration

on Thursday, June 29th, 2017 12:14 | by

 

 

 

 

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Update on Diazepam Experiement(15mM) and T-Maze Experiment

on Friday, June 16th, 2017 4:35 | by

N=20

 

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Update on the Diazepam Experiment

on Thursday, June 1st, 2017 4:05 | by

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Updates on R,S,WTB tests

on Friday, May 26th, 2017 1:20 | by

Rover, N=3

sitter, N=2

wtb, N=4

longterm, N=13 (old WTB excluded)

R,S self learning traces, and longterm memory trace

WTB self learning traces, longterm memory trace

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update on self learning and longterm memory

on Monday, March 27th, 2017 2:07 | by

5 measurements on self learning from rover:

6 measurements on self learning form sitter:

10 measurements on self learning from wtb:

4 measrements on long term test from rover:

(right punishment)

3 measrements on long term test from sitter (fly stops a lot during test, this result may not be accurate):

(13:left punishment, 19: right punishment)

7 measrements on long term test from wtb

(left punishment)

 

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PKG rover update

on Friday, February 24th, 2017 1:48 | by

After adjusting the laser angle, PI got much improved. But, the test 2 phase shows a lower PI than test 1 in most of cases, the reason for that is still unclear. The following is the result of 9 measurements without drifting.

train1 PI: 0.50

train2: 0.42

test1: 0.39

train3:0.61

train4: 0.63

test2: 0.06 ???

 

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