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A Data Dimensionality Reduction Method for Two-dimensional Time-Frequency Data

A data dimension reduction and time-frequency technology, applied in the direction of instruments, computing, character and pattern recognition, etc., can solve the problems that the non-linear characteristics of the data cannot be used, and the recognition rate cannot reach the ideal level.

Active Publication Date: 2020-06-16
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0004] The present invention aims at the situation that when the two-dimensional two-dimensional principal component analysis algorithm reduces the dimensionality of two-dimensional data, the non-linear features contained in the data cannot be used, and the recognition rate cannot reach the ideal situation.

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  • A Data Dimensionality Reduction Method for Two-dimensional Time-Frequency Data
  • A Data Dimensionality Reduction Method for Two-dimensional Time-Frequency Data
  • A Data Dimensionality Reduction Method for Two-dimensional Time-Frequency Data

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Embodiment Construction

[0030] In the following, the algorithm of the present invention is used to reduce the dimensionality of the two-dimensional time-frequency representation data of the wavelet transform of the radar high-resolution range profile to obtain its projection transformation matrix. This embodiment is used to describe the implementation of the present invention in detail, so as to have a deeper understanding of how to apply the technical means of the present invention to solve technical problems, so as to achieve a good solution to practical problems and implement them accordingly. The core two-dimensional principal component analysis algorithm of the present invention, the implementation process of the present invention is as follows figure 1 As shown, each step is specifically implemented as follows:

[0031] Step 1: Center the time-frequency representation of each range image sample A i ∈R m ×R n (i=1,2,...,M, M is the number of time-frequency sample matrix):

[0032] The high-resolutio...

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Abstract

The invention discloses a data dimensionality reduction method for two-dimensional time-frequency data, which is applied to dimensionality reduction and compression of two-dimensional data. The main process of the method: first, center the sample data; then map the centered data to a high-dimensional space, and use the kernel function in the high-dimensional space to construct the covariance of the mapped data; finally, use the bilateral two-dimensional principal component analysis algorithm to Covariance is used for dimensionality reduction to obtain the feature projection transformation matrix. This algorithm not only makes full use of the non-linear features in the original data, but also has fewer coefficients of the feature projection matrix, which not only improves the recognition rate, data compression rate, but also reduces the amount of calculation.

Description

Technical field [0001] The invention relates to the linearization of the nonlinear characteristics of two-dimensional data, and extracts the principal elements of the linearized characteristics, and realizes the dimensionality reduction and reconstruction of the data through the principal elements. Mainly used in target recognition and classification based on two-dimensional image features such as radar time-frequency distribution and facial features. Background technique [0002] Principal Component Analysis (PCA) converts high-dimensional data containing redundant information into a small number of low-dimensional data, namely principal components, where each principal component contains almost all the valid information of the original data. In this way, the intricate data analysis problem is transformed into a problem that only needs to study a few principal components. Not only can the problem be analyzed in more depth, but the analysis process also becomes very easy. The ba...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62
CPCG06F18/2135
Inventor 于雪莲曲学超徐丽唐永昊赵林森
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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