A parallel method is presented for computing the generalized entropies K_q from a time series with a direct approach, i.e. by counting the occurrences of the various box sequences in the phase-space. The parallelization is accomplished by distributing the sequence table among processors, and efficient searching and sorting procedures are employed. A model of the algorithm is used to evaluate computational performance under different operative settings. The algorithm is tested on a distributed memory multiprocessor, the Transtech PARAstation/i860 with eigth nodes; it shows good performance, allowing fast analysis of very long time series.

A parallel searching and sorting method to compute entropies from time series

A Corana;
1996

Abstract

A parallel method is presented for computing the generalized entropies K_q from a time series with a direct approach, i.e. by counting the occurrences of the various box sequences in the phase-space. The parallelization is accomplished by distributing the sequence table among processors, and efficient searching and sorting procedures are employed. A model of the algorithm is used to evaluate computational performance under different operative settings. The algorithm is tested on a distributed memory multiprocessor, the Transtech PARAstation/i860 with eigth nodes; it shows good performance, allowing fast analysis of very long time series.
1996
Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni - IEIIT
9780444824905
nonlinear time series analysis; entropies; searching and sorting; parallel algorithms; distributed memory multiprocessor; message passing
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/317409
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