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Carsten Peterson

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Finding the embedding dimension and variable dependencies in time series

Author

  • Hong Pi
  • Carsten Peterson

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