Application of Minimum Distortion Filtering to Identification of Linear Systems Having Non-uniform Sampling Period

We consider the problem of identification of continuous time systems when the data is collected using non-uniform sampling periods. We formulate this problem in the context of Nonlinear Filtering. We show how a new class of nonlinear filtering algorithm (Minimum Distortion Filtering) can be applied to this problem. A simple example is used to illustrate the performance of the algorithm. We also compare the results with those obtained from (a particular realization) of Particle Filtering.

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