We introduce an algorithm for nonlinear noise reduction which is based on locally linear ts to the nonlinear dynamics. We claim that it is both robust and exible enough to apply it to a variety of experimental time series. In the second part of the paper we show its performance on data set A. The correlation dimension, Liapunov exponent and the Poincar e map are computed before and after the no...

Microarrays are being currently used for the expression levels of thousands of genes simultaneously. They present new analytical challenges because they have a very high input dimension and a very low sample size. It is highly complex to analyse multi-dimensional data with complex geometry and to identify low-dimensional “principal objects” that relate to the optimal projection while losing the...

A crucial element in the practical solution of combustion instability problems in rocket motor development programs is the accurate interpretation of data secured in pulsed motor stability testing. There presently exist no universally accepted or wellestablished methods for carrying out this type of data analysis. Most investigators apply only linear combustion instability theory; any attempted...