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This paper presents a modified version of the twostep
least-mean-square (LMS)-type adaptive algorithm motivated
by the work of Gazor. We describe the nonstationary adaptation
characteristics of this modified two-step LMS (MG-LMS) algorithm
fo
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最小二乘辨识参数，用来辨识非线性系统的参数，还可以对非线性系统进行仿真。-Least squares identification parameters, used to identify nonlinear system parameters, it can also nonlinear system simulation.
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Experience with a real
time implementation of an adaptive power system
stabiliser to damp the dynamic oscillations of a
power system is presented. A multi-input multioutput
(MIMO) pole shifting control algorithm
together with a least-square
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以中等纯度的精馏塔为研究对象，已知系统的传递函数，用matlab仿真，实现最小二乘法对系统进行参数辨识。-In the distillation column medium purity as the research object, the known transfer function of system, using MATLAB simulation, the realization of system parameter identification by the least squa
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用于稀疏系统辨识的L0范约束的最小均方算法原理研究-For sparse system identification of L0 norm constraint of the least mean square algorithm principle is studied
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