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Self-adaptive filtering method based on maximum mixed cross-correlative entropy criterion

A technology of adaptive filtering and adaptive filtering, applied in the field of signal processing, can solve the problems of poor system tracking performance, difficult to stabilize, slow convergence speed, etc., to meet the requirements of fast convergence and fast tracking, wide research significance, good Universal effect

Active Publication Date: 2016-08-17
XI AN JIAOTONG UNIV
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Problems solved by technology

However, the adaptive filtering based on the maximum cross-correlation entropy criterion will lead to a slow convergence speed of the method when the initial error of the filter iteration is relatively large, it is difficult to quickly reach a steady state, and the tracking performance of the system is relatively poor

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  • Self-adaptive filtering method based on maximum mixed cross-correlative entropy criterion
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  • Self-adaptive filtering method based on maximum mixed cross-correlative entropy criterion

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Embodiment Construction

[0031] The present invention will be further described below in conjunction with the drawings.

[0032] See figure 1 , Adaptive filter principle: Based on the estimation of the statistical characteristics of the input and output signals, a specific method is adopted to automatically adjust the filter coefficients to achieve the best filtering characteristics. The adaptive filter can be in the continuous domain or in the discrete domain. The discrete domain adaptive filter is composed of a set of tapped delay lines, variable weighting coefficients and an automatic adjustment coefficient mechanism.

[0033] Attached figure 1 Represents a discrete domain adaptive filter used to simulate the signal flow diagram of an unknown discrete system. The adaptive filter updates and adjusts the weighting coefficients for each sample of the input signal sequence x(n) according to a specific method. If it is in accordance with the minimum mean square error criterion, then the output signal sequen...

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Abstract

The invention provides a self-adaptive filtering method based on a maximum mixed cross-correlative entropy criterion. The method employs the maximum mixed cross-correlative entropy criterion. A cost function is composed of two different kernel bandwidths omega, and used for updating a weight vector w(n+1) so as to modulate a filter to obtain an ideal output signal y(n). The self-adaptive filtering method based on the maximum mixed cross-correlative entropy criterion provided by the invention is composed of two maximum mixed cross-correlative entropies with different kernel bandwidths. The method has the advantages of more rapid primary convergence rate and higher stability precision, and has the capability of rapidly tracing the system variation. The filter designed based on the method is easier to popularize and use in practical use.

Description

Technical field [0001] The invention belongs to the field of signal processing, and relates to an adaptive filtering method based on a maximum mixed cross-correlation entropy criterion. Background technique [0002] In recent years, adaptive filtering has rapidly developed as an optimal filtering method. Adaptive filtering is an optimal filtering method developed on the basis of linear filtering such as Wiener filtering and Kalman filtering. Because it has stronger adaptability and better filtering performance. Therefore, it has been widely used in engineering practice, especially in information processing technology. [0003] In general, the structure of the adaptive filter is not changed. The coefficients of the adaptive filter are time-varying coefficients updated by the adaptive method. That is, its coefficients are automatically and continuously adapted to the given signal to obtain the desired response. The most important feature of an adaptive filter is that it can work...

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Application Information

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IPC IPC(8): H03H21/00
CPCH03H21/0043H03H2021/0076
Inventor 陈霸东邢磊郑南宁
Owner XI AN JIAOTONG UNIV
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