Perfect sequence lms for rapid acquisition of continuous-azimuth head related impulse responses
Perfect sequence lms for rapid acquisition of continuous-azimuth head related impulse responses
复制标题
完美序列 lms，用于快速采集连续方位头相关脉冲响应
DOI：
10.1109/aspaa.2009.5346499
复制
发表时间：
2009
期刊：
影响因子：
--
通讯作者：
Gerald Enzner
中科院分区：
文献类型：
--
作者：
C. Antweiler;Gerald Enzner
在最近的出版物中，连续方位推断的头部相关的脉冲响应（HRIR）被视为一个时变系统识别问题的基础上的动态测量。因此，系统识别可以由LMS型自适应滤波器处理，在本应用中，我们可以自由选择激励信号。为了提供将测量时间减少到最小的前景，我们现在建议在收敛速率方面的最佳激励信号。该激励信号由周期性伪噪声信号的较大族中的完美序列（PSEQ）给出。在讨论了完美序列的具体含义之后，我们将我们的完美序列LMS算法（PSEQ-LMS）的性能与白色噪声处理的结果进行了比较。我们证明了一个统一的改善PSEQ-LMS的工具均方误差分析，以及主观听动态HRIR。这两种措施是一致的。
In recent publications, continuous-azimuth inference of head related impulse responses (HRIRs) was treated as a time-varying system identification problem on the basis of dynamical measurements. The system identification thus can be handled by LMS-type adaptive filters for which we have the freedom to choose the excitation signal in this application. In order to provide the perspective of reducing the measurement time to a minimum, we now suggest the optimal excitation signal in terms of the rate of convergence. This excitation signal is given by perfect sequences (PSEQs) out of the larger family of periodic pseudo-noise signals. After the discussion of specific implications of perfect sequences, we compare the performances of our perfect-sequence LMS algorithm (PSEQ-LMS) to the results of white noise processing. We demonstrate a uniform improvement by PSEQ-LMS in terms of instrumental mean-square error analysis as well as subjective listening to dynamic HRIRs. Both measures turn out to be consistent.