This paper addresses the problem of compression of data sequences for transmission or storage purposes. Self-affine and piecewise self-affine IFS fractal models, estimated by means of Genetic Algorithms, have been used to model different types of discrete sequences. The parameters of such models must be determined accordin to an optimization criterion. However, the general optimization problem is quite complex and some constraints have to be introduced. Several different constraints have been considered in this paper, and the best tradeoff between overall performances and computational complexity has been found. The estimation of the fractal models parameters by means of GAs has shown to be quite robust, and good convergence to the global minimum has been obtained. A comparison with suboptimal algorithms has been included and practical examples has been reported in the paper.

Data Compression by means of fractal models and genetic optimization

MUMOLO, ENZO
1994-01-01

Abstract

This paper addresses the problem of compression of data sequences for transmission or storage purposes. Self-affine and piecewise self-affine IFS fractal models, estimated by means of Genetic Algorithms, have been used to model different types of discrete sequences. The parameters of such models must be determined accordin to an optimization criterion. However, the general optimization problem is quite complex and some constraints have to be introduced. Several different constraints have been considered in this paper, and the best tradeoff between overall performances and computational complexity has been found. The estimation of the fractal models parameters by means of GAs has shown to be quite robust, and good convergence to the global minimum has been obtained. A comparison with suboptimal algorithms has been included and practical examples has been reported in the paper.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2789125
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