Palacín Roca, JordiMarco Colás, SantiagoSamitier i Martí, Josep2009-06-172009-06-1720010018-9456https://hdl.handle.net/2445/8693Multiexponential decays may contain time-constants differing in several orders of magnitudes. In such cases, uniform sampling results in very long records featuring a high degree of oversampling at the final part of the transient. Here, we analyze a nonlinear time scale transformation to reduce the total number of samples with minimum signal distortion, achieving an important reduction of the computational cost of subsequent analyses. We propose a time-varying filter whose length is optimized for minimum mean square error6 p.application/pdfeng(c) IEEE, 2001MostreigData reductionFiltering theoryInterference suppressionLeast mean squares methodsMoving average processesSignal samplingTime-varying filtersTransformsTransient analysisinfo:eu-repo/semantics/article167582info:eu-repo/semantics/openAccess