Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
Multirate systems and filter banks
Multirate systems and filter banks
Automatica (Journal of IFAC)
Linear periodically time-varying discrete-time systems: aliasing and LTI approximations
Systems & Control Letters
Multirate Signal Processing for Communication Systems
Multirate Signal Processing for Communication Systems
Modeling and identification of LPTV systems by wavelets
Signal Processing
Analysis of M-channel time-varying filter banks
Digital Signal Processing
Representations of linear periodically time-varying and multirate systems
IEEE Transactions on Signal Processing
A least-squares approach to blind channel identification
IEEE Transactions on Signal Processing
Cyclic LTI systems in digital signal processing
IEEE Transactions on Signal Processing
Time-varying system identification and model validation usingwavelets
IEEE Transactions on Signal Processing
Linear periodic systems and multirate filter design
IEEE Transactions on Signal Processing
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We derive a new method for the identification of discrete linear periodically time-varying (LPTV) systems. Take an LPTV system with period M, and assume that an input with period N is applied to this system, where N is a multiple of M. The output of this system will be periodic with period N. Using such periodic inputs, we show that we can formulate the problem of identification of LPTV systems in the frequency domain. With the help of the discrete Fourier transform (DFT), the identification method reduces to finding the least-squares (LS) solution of a set of linear equations. We show that the method achieves the Cramer-Rao lower bound (CRLB). A sufficient condition for the identifiability of LPTV systems is given, which can be used to find appropriate inputs for the purpose of identification. Simulation results illustrate the efficiency of the proposed algorithm.