摘要
针对含有未知时滞的多输入单输出有限脉冲响应系统,根据系统参数化后具有的稀疏特性,基于压缩感知原理,将匹配追踪方法和梯度搜索原理相结合,在有限采样数据下,提出了可以同时估计系统参数和时滞的梯度追踪算法.该算法同正交匹配追踪算法相比,梯度追踪算法具有较小的计算量.最后通过仿真验证了算法的有效性.
For multiple-input single-output finite impulse response（ MISO-FIR） systems with unknown time delays,we combine the matching pursuit method and the gradient search principle,according to the sparsity of the parameterized model based on the compressed sensing theory,and propose a gradient pursuit algorithm for simultaneously estimating parameters and time delays with limited sampling data. The proposed method reduces the associated computational burden compared with that of the orthogonal matching pursuit algorithm.The simulation results show the effectiveness of the proposed algorithm.
出处
《信息与控制》
CSCD
北大核心
2016年第2期151-156,共6页
Information and Control
基金
国家自然科学基金资助项目(61304138)
江苏省自然科学基金资助项目(BK20130163)
关键词
梯度追踪
参数辨识
时滞估计
正交匹配追踪算法
gradient pursuit
parameter identification
time-delay estimation
orthogonal matching pursuit algorithm
