Abstract

We proposed in this work the introduction of a new vision of stochastic processes through geometry induced by dilation. The dilation matrices of a given process are obtained by a composition of rotation matrices built in with respect to partial correlation coefficients. Particularly interesting is the fact that the obtention of dilation matrices is regardless of the stationarity of the underlying process. When the process is stationary, only one dilation matrix is obtained and it corresponds therefore to Naimark dilation. When the process is nonstationary, a set of dilation matrices is obtained. They correspond to Kolmogorov decomposition. In this work, the nonstationary class of periodically correlated processes was of interest. The underlying periodicity of correlation coefficients is then transmitted to the set of dilation matrices. Because this set lives on the Lie group of rotation matrices, we can see them as points of a closed curve on the Lie group. Geometrical aspects can then be investigated through the shape of the obtained curves, and to give a complete insight into the space of curves, a metric and the derived geodesic equations are provided. The general results are adapted to the more specific case where the base manifold is the Lie group of rotation matrices, and because the metric in the space of curve naturally extends to the space of shapes; this enables a comparison between curves’ shapes and allows then the classification of random processes’ measures.

Highlights

  • The analysis and/or the representation of nonstationary processes has been tackled for four or five decades by time-scale/time-frequency analysis [1,2], by Fourier-like representation when the processes belong to the periodically correlated (PC) subclass [3,4], or by partial correlation coefficients series [5,6], to cite a few

  • The dilation theory corresponds to Naimark dilation [17,18], and states that given a sequence of correlation coefficients, there exists a unitary matrix W such that

  • We have introduced a new vision of stochastic processes through geometry induced by dilation

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Summary

Introduction

The analysis and/or the representation of nonstationary processes has been tackled for four or five decades by time-scale/time-frequency analysis [1,2], by Fourier-like representation when the processes belong to the periodically correlated (PC) subclass [3,4], or by partial correlation coefficients (parcors) series [5,6], to cite a few. One of the advantages of dealing with parcors resides in their strong relation to the measure of the process by the one-to-one relation with correlation coefficients [7,8]. They appear explicitly in the Orthogonal Polynomial on the Real Line/Unit Circle decomposition of the measure [9,10], on the Matrices Orthogonal Polynomials on the Unit Circle [11]. The dilation theory corresponds to Naimark dilation [17,18], and states that given a sequence of correlation coefficients, there exists a unitary matrix W such that. When the process is not stationary, its associated correlation matrix is no more Toeplitz structured, a set of matrices is required [16]

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