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An implementation of the Cohen’s class time-frequency distributions on a massively parallel processor

Konopko K.

Przegląd Elektrotechniczny

2012

R. 88, nr 9b

289-291

A time-frequency signal analysis (TFSA) refers to processing of signals with a time-varying frequency content. These non-stationary signals are best represented by the time-frequency distributions, which show how the energy of the signal is distributed over a two-dimensional timefrequency space. Real time processing of these non-stationary signals demands the computational performance of a few giga operations per second, which cannot be obtained using the single or multi core processors. The required computing power can be provided by the massively parallel processors. The paper presents an implementation of the Cohen’s class time-frequency representations on a massively parallel processor.

Łączne czasowo-częstotliwościowe reprezentacje sygnałów umożliwiają analizowanie sygnałów, których widmo częstotliwościowe zmienia się w czasie. Przetwarzanie, w czasie rzeczywistym, sygnałów niestacjonarnych wymaga jednak znacznej mocy obliczeniowej. W artykule przedstawiono efektywną implementację czasowo-częstotliwościowej reprezentacji sygnałów z zastosowaniem procesorów masowo-równoległych.

Algorithms for parallel processor scheduling with distinct due windows and unit-time jobs

Janiak A., Janiak W.A., Januszkiewicz R.

Bulletin of the Polish Academy of Sciences. Technical Sciences

2009

Vol. 57, nr 3

209-215

We have studied problems of scheduling n unit-time jobs on m identical parallel processors, in which for each job a distinct due window is given in advance. If a job is completed within its due window, then it incurs no penalty. Otherwise, it incurs a job-dependent earliness or tardiness cost. The objective is to find a job schedule such that the total weighted earliness and tardiness, maximum weighted earliness and tardiness or total weighted number of early and lardy jobs is minimized. Properties of optimal solutions of these problems are established. We proved that optimal solutions for these problems can be found in O(n5) time in case of minimization of the total weighted earliness and tardiness and the total weighted number of early and tardy jobs and in O (n4 n log n) time in case of minimization of the maximum weighted earliness and tardiness. The established solution methods are extended to solve the problems with arbitrary integer release dates. A dedicated algorithm with time complexity O(n3) is provided for the special case of the problem of minimizing total weighted number of early and tardy jobs with agreeable earliness-tardiness weights.