Title :
Using iterated function systems to model discrete sequences
Author :
Mazel, David S. ; Hayes, Monson H.
fDate :
7/1/1992 12:00:00 AM
Abstract :
Two iterated function system (IFS) models are explored for the representation of single-valued discrete-time sequences: the self-affine fractal model and the piecewise self-affine fractal model. Algorithms are presented, one of which is suitable for a multiprocessor implementation, for identification of the parameters of each model. Applications of these models to a variety of data types are given where signal-to-noise ratios are presented, quantization effects of the model parameters are investigated, and compression ratios are computed
Keywords :
data compression; fractals; identification; iterative methods; signal processing; compression ratios; identification; iterated function systems; piecewise self-affine fractal model; quantization effects; signal processing; signal-to-noise ratios; single-valued discrete-time sequences; Data compression; Extraterrestrial measurements; Filters; Fractals; Inverse problems; Laboratories; Least squares methods; Polynomials; Quantization; White noise;
Journal_Title :
Signal Processing, IEEE Transactions on
