We present a method of parameter estimation for large class of nonlinear systems, namely those in which the state consists of output derivatives and the flow is linear in the parameter. The method, which solves for the unknown parameter by directly inverting the dynamics using regularized linear regression, is based on new design and analysis ideas for differentiation filtering and regularized least squares. Combined in series, they yield a novel finite-sample bound on mean absolute error of estimation.

翻译：本文提出了一种适用于一大类非线性系统的参数估计方法，该类系统的状态由输出导数构成且动态方程关于参数呈线性。该方法通过正则化线性回归直接对动态方程求逆来求解未知参数，其核心在于微分滤波与正则化最小二乘的新颖设计与分析思路。将二者串联使用，我们首次得到了估计值平均绝对误差的有限样本界。