Data compression for subspace-based identification using periodic inputs

In this paper we develop data compression techniques for subspace methods to extend their ability to work with long data records. Satisfactory results are obtained when a subspace algorithm is used to identify the system based on averaged measurements with periodic input signals. We also discuss pitfalls of using multitonal input signals in combination with the proposed scheme.