Continuous-Time System Identification for Linear and Nonlinear Systems Using Wavelet Decompositions

A new approach for estimating linear and nonlinear continuous-time models directly from noisy observations is introduced using wavelet decompositions. Results using both simulated and experimental data are included to demonstrate the performance of the new algorithm.