Adaptive linearization schemes for weakly nonlinear systems using adaptive linear and nonlinear FIR filters
Adaptive linearization schemes for weakly nonlinear systems using adaptive linear and nonlinear FIR filters
复制标题
使用自适应线性和非线性 FIR 滤波器的弱非线性系统的自适应线性化方案
DOI：
10.1109/mwscas.1990.140639
复制
发表时间：
1990
期刊：
影响因子：
--
通讯作者：
W. Snelgrove
中科院分区：
文献类型：
--
作者：
X. Y. Gao;W. Snelgrove
提出了三种自适应线性化方案。在第一个方案中，通过消除物理系统输出处的非线性来执行线性化。在第二种方法中，采用非线性后处理器对信号进行后失真处理。第三种是使用预处理器。使用后处理器和预处理器的方案是为弱非线性系统设计的，而通过输出取消来线性化的方案可以应用于具有更强非线性的问题。在所有三种方法中，线性和非线性算子的必要估计由自适应线性和非线性滤波器提供。给出了由具有线性项、二次项和三次项的 Volterra 级数建模的物理系统的典型模拟结果，并且被认为是令人鼓舞的。<<ETX>>
Three adaptive linearization schemes are proposed. In the first scheme, linearization is performed by canceling nonlinearity at the output of a physical system. In the second, a nonlinear postprocessor is employed to postdistort signals. In the third, a preprocessor is used. The schemes using a postprocessor and a preprocessor are designed for weakly nonlinear systems, whereas the scheme of linearization by cancellation at the output can be applied to problems with stronger nonlinearities. In all three methods, necessary estimates of linear and nonlinear operators are provided by adaptive linear and nonlinear filters. Typical simulation results for a physical system modeled by a Volterra series with a linear term, a quadratic term, and a cubic term are presented and are judged encouraging.<<ETX>>