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For image representation methods of image classification, it is very important to represent the image well. In this paper, we propose a novel representation method for image classification, which can combine the advantage that the sparse representation can effectively use image information and the advantage that the PCA method can effectively eliminate the interference of irrelevant image information, and overcome the shortcomings of them. The proposed method firstly used the PCA method to obtain the first numbers of eigenvectors with the largest contribution rate for the samples of each subject as the training samples, and then these training samples are used to represent the test sample.

Micro-quadrotor has recently been used in different areas even military field. However, controlling mini-quadrotor to flight attitude in the air has not been perfectly achieved due to mini-quadrotor's small size and light weight. The purpose of this paper is to introduce the flight attitude control system of mini-quadrotor, including design and simulation of calculations and controllers. By using distributed multi-sensors, the attitude and horizontal position information of mini-quadrotor is obtained. The simulation of the attitude controller is applied with the MATLAB Simulink library. In conclusion, the designed attitude controller can make mini-quadrotor have smooth flight and move in all directions and enable the mini-quadrotor to properly flight.