CAJ | 학술논문

提升小波变换用于混沌信号降噪具有良好的效果，阈值选取与混沌信号降噪后信号的畸变具有紧密联系。为了提高混沌信号中提升小波的自适应能力，降低降噪后信号的畸变率，提出了一种基于提升小波和粒子群相结合的混沌信号降噪方法。该方法在对提升小波变换后的细节部分进行阈值处理时，采用阈值自适应选择方法，并结合粒子群算法全局搜索最优阈值。通过对Colpitts模型进行仿真分析，与标准的软阈值降噪相比，能更好地对混沌信号降噪，并且降噪后信号失真度较小，具有很好的应用价值。
제승소파변환용우혼돈신호강조구유량호적효과，역치선취여혼돈신호강조후신호적기변구유긴밀련계。위료제고혼돈신호중제승소파적자괄응능력，강저강조후신호적기변솔，제출료일충기우제승소파화입자군상결합적혼돈신호강조방법。해방법재대제승소파변환후적세절부분진행역치처리시，채용역치자괄응선택방법，병결합입자군산법전국수색최우역치。통과대Colpitts모형진행방진분석，여표준적연역치강조상비，능경호지대혼돈신호강조，병차강조후신호실진도교소，구유흔호적응용개치。
Lifting wavelet transform are efficient for chaotic signal noise reduction. Threshold estimation is closely related to chaotic signals de-noised by wavelet shrinkage methods. An adaptive wavelet threshold algorithm for de-noising of chaotic signals is put forward in order to improve the adaptive property of wavelet de-noising and to reduce distortion of de-noised signal. The wavelet de-nosing algorithm is based on an optimum and adaptive shrink-age scheme. A class of shrinkage functions with continuous derivatives and PSO is used for the adaptive shrinkage scheme. The de-noising result of simulative chaotic signals is presented. The chaotic signals de-noised by the adap-tive wavelet threshold algorithm can remove the white noise effectively and have smaller distortion in waveform than the signals de-noised by using the standard soft shrinkage scheme. This method has good value in practical chaotic online monitoring.