User:Simonjung/Multiple alignment of continuous data

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Multiple Alignment of Continuous Data ...

When observing multiple time series generated by a noisy, stochastic process, large systematic sources of variability are often present. For example, within a set of nominally replicate time series, the time axes can be variously shifted, compressed and expanded, in complex, non-linear ways. Additionally, in some circumstances, the scale of the measured data can vary systematically from one replicate to the next, and even within a given replicate.

References

^[1]

^ Listgarten, Jennifer (2005). "Multiple Alignment of Continuous Time Series". Advances in Neural Information Processing Systems. 17. {{cite journal}}: Unknown parameter |coauthors= ignored (|author= suggested) (help)

External links

Continuous Profile Models (CPM) Matlab Toolbox by Jennifer Listgarten

[1] Listgarten, Jennifer (2005). "Multiple Alignment of Continuous Time Series". Advances in Neural Information Processing Systems. 17. {{cite journal}}: Unknown parameter |coauthors= ignored (|author= suggested) (help)

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