CAJ | 학술논문

利用信号频谱幅度分布的先验信息，对短时数据序列信号提出了一种实现高分辨率谱估计和数据序列外推的快速算法。该算法利用了算子矩阵的特殊结构，采用简单、快速的矩阵求逆算法，使算法的运算量和数据存储容量大幅度下降。给出了算法在高分辨率谱估计及数据序列外推中的应用实例和仿真结果，证实了该算法的优良性能。
이용신호빈보폭도분포적선험신식，대단시수거서렬신호제출료일충실현고분변솔보고계화수거서렬외추적쾌속산법。해산법이용료산자구진적특수결구，채용간단、쾌속적구진구역산법，사산법적운산량화수거존저용량대폭도하강。급출료산법재고분변솔보고계급수거서렬외추중적응용실례화방진결과，증실료해산법적우량성능。
In this paper, a fast algorithm of high-resolution spectral estimation and data sequences extrapolation for short-time data sequences is proposed by using the prior distribution of spectral amplitudes. This algorithm which computes the inversion of operator matrix is simple and fast based on the special structure of operator matrix. The computational load and the number of data memory units of the algorithm can be efficiently reduced. The paper also gives out the application examples and computer simulation results that demonstrate the excellent performance of high-resolution spectral estimation and data sequences extrapolation.