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Gaussian Processes for Prediction of Homing Pigeon Flight Trajectories

Abstract:

We construct and apply a stochastic Gaussian Process (GP) model of flight trajectory generation for pigeons trained to home from specific release sites. The model shows increasing predictive power as the birds become familiar with the sites, mirroring the animal's learning process. We show how the increasing similarity between successive flight trajectories can be used to infer, with increasing accuracy, an idealised route that captures the repeated spatial aspects of the bird's flight. We su...

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Publication status:
Published

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Publisher copy:
10.1063/1.3275635

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Volume:
1193
Pages:
360-367
Host title:
BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING
Publication date:
2009-01-01
DOI:
EISSN:
1551-7616
ISSN:
0094-243X
Source identifiers:
210373
ISBN:
9780735407299
Keywords:
Pubs id:
pubs:210373
UUID:
uuid:68e921a9-c825-49e0-b347-91e512b7847d
Local pid:
pubs:210373
Deposit date:
2012-12-19

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