摘要
对比了Gabor和Chirplet字典中的时频原子,研究了Chirplet时频字典中的子空间匹配追踪算法.该算法由时频分布确定chirp原子的时频中心,然后在时频中心保持不变的条件下搜索原子的尺度和调频率.同Gabor字典中的标准匹配追踪算法、子空间匹配追踪算法相比,Chirplet字典中的子空间匹配追踪算法对信号的逼近所需原子数更少,对实测语音信号的数值计算证实了这一点.
Based on the comparison of TF atoms in the Gabor and Chirplet dictionaries, the subspace matching pursuit algorithm in the Chirplet dictionary is researched in this paper. In the algorithm, the time -frequency centers of the chirp atoms are determined by the pilot TF distribution and then the scale factor and chirp rate is estimated under the precondition of keeping time -frequency center unchangeable. Compared with the matching pursuit and subspace matching pursuit in the Gabor dictionary, the proposed algorithm requires less TF atoms to approximate a signal, which is verified by the numerical results of real speech signals.
出处
《昆明理工大学学报（理工版）》
北大核心
2010年第3期89-92,共4页
Journal of Kunming University of Science and Technology(Natural Science Edition)
基金
国家自然科学基金(10901074)
江西省自然科学基金(2008GQS0054)
