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Blind source separation method based on quantum rhinoceros search mechanism

A blind source separation and quantum technology, applied in the direction of quantum computers, computer components, instruments, etc., can solve problems such as the inability to achieve fast and high-precision blind source separation, so as to avoid excessive calculation, avoid the curse of dimensionality, and accelerate convergence speed effect

Active Publication Date: 2020-12-04
HARBIN ENG UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to overcome the problem that the existing independence criterion cannot be guaranteed to be the optimal criterion faced by the traditional blind source separation method, and the existing solution method is only to optimize the low-dimensional objective function or high-dimensional objective function Function optimization can not achieve fast and high-precision blind source separation engineering problems, and then provide a more effective and stable blind source separation method based on the quantum rhinoceros search mechanism

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  • Blind source separation method based on quantum rhinoceros search mechanism
  • Blind source separation method based on quantum rhinoceros search mechanism
  • Blind source separation method based on quantum rhinoceros search mechanism

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Embodiment Construction

[0050] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0051] For the convenience of description, the blind source separation method based on the quantum rhino search algorithm is abbreviated as QRSA-BSS, and the blind source separation method based on the particle swarm optimization algorithm is abbreviated as PSO-BSS.

[0052] Negentropy function coefficient χ=48.

[0053] The parameters of QRSA-BSS are set as follows: male quantum rhino population size M m =30; female quantum rhino population size M f =30;α max = β max =0.1; in the simplified iterative model, d 1 = 3, θ=[θ 1 ,θ 2 ,θ 3 ] respectively represent the rotation angles of three different rotation matrices, θ 1 ,θ 2 ,θ 3 ∈[0,2π); The rotation angle search interval is between 0 degrees and 360 degrees, so In the nonreduced iterative model, d 2 =9, Discovery probability p 1 =0.3,p 2 =0.9; inertia weight co...

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Abstract

The invention provides a blind source separation method based on a quantum rhinoceros search mechanism, and designs a hybrid optimization objective function designed based on two different independence criteria, i.e., the hybrid optimization objective function is designed based on two independence criteria of maximization kurtosis and maximization negentropy, and the two criteria are endowed withcorresponding weight coefficients. The optimal criterion of the intelligent calculation method can be judged according to the change condition of the hybrid optimization objective function value alongwith the weight coefficient, so that a more accurate blind source separation result is obtained. Furthermore, a blind source separation method based on a quantum rhinoceros search mechanism and a hybrid optimization objective function is designed. The method designed by the invention can realize blind source separation of aliasing signals, has the advantages of the high convergence speed, high separation precision, stable performance and the like, and has a wide application prospect.

Description

technical field [0001] The invention relates to a blind source separation method based on a quantum rhino search mechanism, belonging to the field of blind source separation. Background technique [0002] Blind source separation research is a signal processing method that only extracts or restores the components of the source signal from the observed mixed signal when the prior knowledge of the source signal and the transmission channel are unknown. Blind source separation is essentially a signal processing method, which is applicable to various information fields, including wireless communication, image processing, and speech recognition, etc., especially in signal processing, artificial neural networks, etc., and has extremely important research value. With the continuous deepening of the research on the blind signal problem for many years, the blind source separation technology has obtained many research results, and has become a hot research topic in the field of signal ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/00G06N10/00
CPCG06N3/006G06N10/00G06F18/21
Inventor 高洪元张志伟臧国建王世豪张世铂马静雅李慧爽杨杰邹一凡
Owner HARBIN ENG UNIV
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