Electronic nose feature selection optimization method on basis of multiple Fisher kernel discriminant analysis

A technique of discriminant analysis and feature selection, applied in character and pattern recognition, instruments, computer components, etc., can solve problems such as sensor redundancy and poor data discrimination

Active Publication Date: 2015-04-08
SOUTHWEST UNIVERSITY
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Problems solved by technology

[0007] Aiming at the deficiencies of the prior art, the purpose of the present invention is to provide a method for processing electronic nose signals based on multi-kernel Fisher discriminant analysis. Using this method for fea

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  • Electronic nose feature selection optimization method on basis of multiple Fisher kernel discriminant analysis
  • Electronic nose feature selection optimization method on basis of multiple Fisher kernel discriminant analysis
  • Electronic nose feature selection optimization method on basis of multiple Fisher kernel discriminant analysis

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[0029] The specific implementation manner and working principle of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0030] The electronic nose data used in this example were collected from 20 6-8 week old male Sprague-Durer rats with a body weight of 225-250 grams. Each experiment was carried out under normal pressure, constant temperature and the same indoor environment humidity. under the conditions. In addition, all male Sprague-Dürer rats were in the same class for size, weight, and health.

[0031] Data collection: 20 rats were randomly divided into four groups, including one non-infected group and three infected groups infected with Pseudomonas aeruginosa, Escherichia coli and Staphylococcus aureus respectively. In the first step of the experimental stage, a small mouth about 1 cm in length was cut out in the hind leg of each mouse, and then 10 9 CFU / mL of Pseudomonas aeruginosa or Escherichia coli or Stap...

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Abstract

The invention discloses an electronic nose feature selection optimization method on the basis of multiple Fisher kernel discriminant analysis. The electronic nose feature selection optimization method comprises the following steps: firstly, acquiring a sample feature matrix; initializing parameters and establishing a fundamental kernel function according to the parameters; then calculating a composite kernel matrix on the basis of a fundamental kernel matrix, calculating a projection of the composite kernel matrix in a high-position feature space, then feeding the projection into a classifier to carry out mode identification to determine a kernel function with the highest identification rate; finally, on the basis of the kernel function, calculating a projection of a new sample matrix in the feature space, using the projection as an electronic nose signal and using the electronic nose signal as an input of the classifier to carry out mode identification. The electronic nose feature selection optimization method has the obvious effects of solving the problem of poor data discrimination after high-dimension projection is implemented by a single kernel function method, solving the problem of redundancies between sensors, optimizing a sensor array, reducing data dimensions and improving the identification rate of the electronic nose signal so as to provide beneficial guide for a doctor to select a suitable treatment method.

Description

technical field [0001] The invention relates to the technical field of electronic nose signal processing, in particular to an electronic nose feature selection optimization method based on multi-core Fisher discriminant analysis. Background technique [0002] An electronic nose is an electronic system that uses the response map of a gas sensor array to identify odors, and it can continuously and real-time monitor the odor status of a specific location within hours, days or even months. [0003] Medical electronic nose is a special electronic nose system, which can realize the diagnosis of disease or wound infection by detecting the gas exhaled by the patient or the gas in the head space of the wound. It has short response time, fast detection speed, low cost, simple and convenient operation, and has the advantages of artificial intelligence, so it has gained wide attention and application. [0004] After the electronic nose feature extraction, it needs to be used as the inp...

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Application Information

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IPC IPC(8): G06K9/64G06K9/46
CPCG06V10/40G06F18/2411
Inventor 闫嘉段书凯王丽丹贾鹏飞
Owner SOUTHWEST UNIVERSITY
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