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FIR filter design method based on particle swarm optimization

A technology of filter design and particle swarm algorithm, applied in the direction of impedance network, digital technology network, electrical components, etc., can solve the problems of single factor, not considering other performances of FIR filter, difficult to guarantee the filtering effect, etc., to speed up the search speed , reduce the probability of falling into a local optimal position, and better adapt to the effect of external interference

Inactive Publication Date: 2016-11-02
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

Both of these criteria are considered and only focus on the degree of approximation between the filter to be designed and the ideal low-pass filter. The factors considered are relatively simple, and other properties of the FIR filter, such as the signal-to-noise ratio, are not considered. When the input When the interference of the signal changes, it is difficult to guarantee the filtering effect

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  • FIR filter design method based on particle swarm optimization
  • FIR filter design method based on particle swarm optimization
  • FIR filter design method based on particle swarm optimization

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[0028] Since FIR filter design can be regarded as an optimization problem, the present invention adopts particle swarm algorithm to realize the design of FIR filter, and based on the consideration of signal-to-noise ratio of the filtered signal, the fitness function is improved. figure 1 It is a flow chart of the FIR filter design method based on the particle swarm algorithm of the present invention. Such as figure 1 Shown, the FIR filter design method based on particle swarm algorithm of the present invention comprises the following steps:

[0029] S101: setting particle swarm optimization algorithm parameters:

[0030] First of all, it is necessary to set the parameters in the particle swarm algorithm, including particle swarm size M, the maximum number of iterations G max and fitness threshold F min . The system function of the FIR filter can be written as:

[0031]

[0032] Among them, h(n) represents the unit impulse response of the FIR filter, and N represents th...

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Abstract

The invention discloses a FIR filter design method based on particle swarm optimization. The method is characterized by using the unit impulse response of a FIR filter as the particle position vector of the particle swarm optimization; designing the fitness function of the particle swarm optimization on the basis of a signal-to-noise ratio of a signal filtered by the FIR filter and the mean square error of the FIR filter and obtaining the FIR filter by iteration. The method designs the fitness function of the particle swarm optimization based on minimized signal-to-noise ratio and mean square error, and designs the FIR filter based on particle swarm optimization so as to achieve the FIR filter taking account of signal-to-noise ratio performance.

Description

technical field [0001] The invention belongs to the technical field of filter design, and more specifically relates to a method for designing an FIR filter based on a particle swarm algorithm. Background technique [0002] FIR (Finite Impulse Response, finite-length unit impulse response) filter, also known as a non-recursive filter, is the most basic component in a digital signal processing system. It can guarantee any amplitude-frequency characteristics while having strict linear phase frequency characteristics, and its unit sampling response is finite, so the filter is a stable system. Therefore, FIR filters are widely used in communication, image processing, pattern recognition and other fields. [0003] At present, the commonly used FIR filter design methods include window function method, frequency sampling method and optimal design method of ripple approximation such as Chebyshev. In practical engineering applications, the design and implementation of FIR filters us...

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Application Information

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IPC IPC(8): H03H17/00
CPCH03H17/00H03H2017/0081
Inventor 王锂戴志坚马敏张永友
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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