On comparing and clustering the spectral densities of several almost cyclostationary processes
Mohammad Reza Mahmoudi, Mohsen Maleki, К. I. Borodin, Kim-Hung Pho, Dumitru Bǎleanu
Abstract
In time series analysis, comparing spectral densities of several processes with almost periodic spectra is an interested problem. The contribution of this work is to give a technique to compare and to cluster the spectral densities of some independent almost periodically correlated (cyclostationary) processes. This approach is based on the limiting distribution for the periodogram and the discrete Fourier transform. The real world examples and simulation results indicate that the approach well acts.
Topics & Concepts
Cyclostationary processPeriodogramStatistical physicsSeries (stratigraphy)MathematicsFourier transformCluster analysisCluster (spacecraft)LimitingSpectral clusteringDistribution (mathematics)Spectral density estimationSpectral densitySpectral lineDiscrete Fourier transform (general)StatisticsAlgorithmComputer scienceFourier analysisPhysicsMathematical analysisEngineeringShort-time Fourier transformTelecommunicationsAstronomyPaleontologyMechanical engineeringChannel (broadcasting)Programming languageBiologyTime Series Analysis and ForecastingComplex Systems and Time Series AnalysisBlind Source Separation Techniques