Title :
Multiscale statistical signal processing: identification of a multiscale AR process from a sample of an ordinary signal
Author_Institution :
IRISA, Rennes, France
fDate :
12/1/1993 12:00:00 AM
Abstract :
The theory of stochastic processes on homogeneous trees aims at contributing to the theory of multiresolution stochastic modeling and associated techniques of multiscale statistical signal processing. The author solves the problem of identifying such a multiscale process indexed by the nodes of a tree from the observation of this process on one single level of resolution. In particular he considers multiscale autoregressive processes, which are evolving by descending on a “hanging” homogeneous tree
Keywords :
signal processing; stochastic processes; trees (mathematics); homogeneous tree; homogeneous trees; multiresolution stochastic modeling; multiscale AR process identification; multiscale autoregressive processes; multiscale statistical signal processing; nodes; stochastic processes; Autoregressive processes; Discrete wavelet transforms; Helium; Sensor fusion; Signal processing; Signal resolution; Stochastic processes; Tree data structures; Wavelet analysis; Wavelet transforms;
Journal_Title :
Signal Processing, IEEE Transactions on