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Carsten Peterson
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Finding the embedding dimension and variable dependencies in time series
Author
Summary, in English
We present a general method, the δ-test, which establishes functional dependencies given a sequence of measurements. The approach is based on calculating conditional probabilities from vector component distances. Imposing the requirement of continuity of the underlying function, the obtained values of the conditional probabilities carry information on the embedding dimension and variable dependencies. The power of the method is illustrated on synthetic time-series with different time-lag dependencies and noise levels and on the sunspot data. The virtue of the method for preprocessing data in the context of feedforward neural networks is demonstrated. Also, its applicability for tracking residual errors in output units is stressed.
Department/s
- Computational Biology and Biological Physics - Has been reorganised
Publishing year
1994
Language
English
Pages
509-520
Publication/Series
Neural Computation
Volume
6
Issue
3
Document type
Journal article
Publisher
MIT Press
Topic
- Other Physics Topics
Status
Published
ISBN/ISSN/Other
- ISSN: 1530-888X