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：我们提出了一类非线性系统（即状态由输出导数构成且流形关于参数呈线性的系统）的参数估计方法。该方法通过正则化线性回归直接对动力学方程求逆以求解未知参数，其基础是微分滤波与正则化最小二乘的新颖设计与分析思路。将两者串联后，我们得到了估计均方绝对误差的全新有限样本界。