CAJ | 학술논문

采用小波分解可以很好地研究信号的自相似性。小波变换能够分析信号奇异点的位置及奇异性强弱，即通过小波变换后的局部极大值在不同尺度上的衰减特性来衡量信号的奇异性。介绍了小波变换的基本概念，对信号特征和突变点检测算法进行研究，利用小波多分辨分析将突变信号进行多尺度分解，通过分解的信号确定突变点位置。通过 Matlab实验，分析了信号奇异点定位和小波检测的结果，当小波变换尺度越精细时，检测突变点位置越精确，验证了小波变换是分析信号自相似性和突变点检测的有力工具。
채용소파분해가이흔호지연구신호적자상사성。소파변환능구분석신호기이점적위치급기이성강약，즉통과소파변환후적국부겁대치재불동척도상적쇠감특성래형량신호적기이성。개소료소파변환적기본개념，대신호특정화돌변점검측산법진행연구，이용소파다분변분석장돌변신호진행다척도분해，통과분해적신호학정돌변점위치。통과 Matlab실험，분석료신호기이점정위화소파검측적결과，당소파변환척도월정세시，검측돌변점위치월정학，험증료소파변환시분석신호자상사성화돌변점검측적유력공구。
Wavelet decomposition is a good way to study self-similarity of signals.Wavelet transform can analyze the location and strength of the signal singularity,which can measure the sigularity of the sig-nals through the attenuation characteristics of local maximum value after wavelet transform at different scales.This paper introduces the basic concepts of wavelet transformation,studies the characteristics of signals and mutation point detection algorithm.This paper uses the characteristics of wavelet multiresolu-tion to decompose singularity signals,and locates the singularity positions of singularity signals using the decomposed signals.By MATLAB,this paper analyzes the locating singularity points and results detection of wavelet.The wavelet transform scales is fine,the detecting mutation point position is more accurate, which verifies that the wavelet transform is a powerful tool for signal self-similarity and mutation detec-tion.