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Orthogonal mirror image filter group realizing method and device based on genetic algorithm

A filter bank and genetic algorithm technology, applied in the field of genetic algorithm, can solve the problems of large amount of calculation, large amount of storage, increase of reconstruction error of QMF group, etc., to simplify the implementation process, reduce the amount of storage, and reduce the amplitude distortion. Effect

Inactive Publication Date: 2007-11-07
VIMICRO CORP
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Problems solved by technology

[0012] In the existing genetic algorithm, the individuals generated in each iteration process must be stored and crossover and mutation operations are performed, so there are problems of large calculation and storage, which is not conducive to the real-time realization of the algorithm
Therefore, when this genetic algorithm is applied to the QMF group, the reconstruction error of the QMF group will be increased, resulting in a large amplitude distortion

Method used

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  • Orthogonal mirror image filter group realizing method and device based on genetic algorithm
  • Orthogonal mirror image filter group realizing method and device based on genetic algorithm
  • Orthogonal mirror image filter group realizing method and device based on genetic algorithm

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Embodiment Construction

[0030] Embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0031] In order to make the QMF group close to the goal of accurate reconstruction, the amplitude distortion algorithm can be optimized to reduce the reconstruction error of the QMF group and achieve the goal of close to accurate reconstruction. The embodiment of the present invention provides a method for implementing a QMF group based on a genetic algorithm, thereby achieving the purpose of minimizing reconstruction errors.

[0032] Referring to Fig. 2, it is a schematic flow chart of the genetic algorithm of the embodiment of the present invention, and the specific steps include:

[0033] Step 201, initialization process, including setting the initial value of gene selection probability and the adjustment value of gene selection probability.

[0034] Initially, the probability of selecting "1" for all genes on the bits is P i =0.5 (that is, it is ...

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Abstract

A method for realizing orthogonal mirror image filter set based on genetic algorithm includes generating multi-set of random number to represent parameter of orthogonal mirror image filter set, coding each set of random number to binary system character string in finite length according to current gene selection probability, decoding each character string and calculating out adaptive degree, updating said probability according to gene of character string with highest adaptive degree, repeating said step till ending condition is satisfied, obtaining parameter of said filter set by decoding character string with highest adaptive degree and utilizing obtained parameter to realize said filter set.

Description

technical field [0001] The invention relates to genetic algorithm technology, in particular to a method for realizing an orthogonal mirror filter bank based on genetic algorithm and an optimization device for parameters of the orthogonal mirror filter bank. Background technique [0002] Genetic Algorithms (GA) is a parallel stochastic optimization algorithm proposed by simulating natural inheritance and Darwinian evolution theory in biology, and its purpose is to obtain the optimal solution. In the genetic algorithm, all parameters of the optimization problem are encoded to form a finite-length binary string, and the string is called "individual". The basic genetic unit of biological individuals in the biological world is the gene, and the genetic genes are arranged in a certain order to form chromosomes. In the genetic algorithm, the chromosome corresponds to the finite length string representing the individual, and the genetic gene corresponds to the value of each bit of t...

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Application Information

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IPC IPC(8): H03H17/00G06N3/12
Inventor 张晨冯宇红
Owner VIMICRO CORP
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