Gustatory induction signal variation feature extraction method based on kernel linear discriminant analysis

Abstract

The invention provides a gustatory induction signal variation feature extraction method based on kernel linear discriminant analysis. The method comprises the following steps: obtaining sensor response sequential signals by detecting tea samples by use of an electronic tongue; according to the response sequential signals, analyzing and rejecting abnormal samples by use of a main component residual error and Mahalanobis distance method; optimizing parameters of a kernel linear discriminant analysis method, and taking a Longjing tea quality grade correct recognition rate as a basis, selecting parameters of the kernel linear discriminant analysis; obtaining taste features of tea samples by performing nonlinear feature extraction on the sensor response signals by use of the kernel linear discriminant analysis method; and inputting the taste features of the tea samples into a classifier, and carrying out teat quality grade determination. According to the invention, abnormal value rejection is performed on the tea samples, nonlinear features of the tea samples with different grades can be represented better by use of the kernel linear discriminant analysis method after parameter optimization, and signal variation of the samples after nonlinear mapping in a high-dimensional feature space is improved.

Description

Technical field [0001] The invention relates to the technical field of tea detection, in particular to a method for extracting distinctive features of taste induction signals based on nuclear linear discriminant analysis. Background technique [0002] In recent years, tea quality testing has been a very difficult task because tea contains many ingredients and their effects on tea quality are very different. West Lake Longjing tea is a typical representative of Chinese green tea. Some vendors, in order to seek their own interests, fry other green tea into a flat shape to pretend to be Longjing tea, or use Longjing from other places in Zhejiang to pretend to be West Lake Longjing, disrupting the Longjing tea market and damaging the interests of consumers. Scientific testing and evaluation are of great significance. [0003] For a long time, sensory evaluation is an important method to evaluate the quality of tea, but this method requires a wealth of tea knowledge and evaluation exp...

AI Technical Summary

Problems solved by technology

However, traditional linear feature extraction methods cannot effectively explore the inherent laws existing in nonlinear data.

Images