Brief paper: Synthesis of linear stochastic signals in identification problems

Authors:
B. R. Upadhyaya;H. W. Sorenson
Affiliations:
Department of Nuclear Engineering, The University of Tennessee, Knoxville, TN 37916, U.S.A.;Department of Applied Mechanics and Engineering Science, University of California, San Diego, La Jolla, CA 92093, U.S.A.
Venue:
Automatica (Journal of IFAC)
Year:
1977

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Abstract

Stationary stochastic inputs are generated from linear processes of the autoregressive moving average type. Since the spectral density of such an input process is nonzero everywhere, this belongs to the class of admissible signals satisfying identifiability requirements. A characterization of the optimal signals is obtained in terms of their spectral densities using the results on asymptotic eigenvalue distribution of Toeplitz matrices. These signals belong to the general class of random inputs that can be generated using standard instrumentation consisting of delay lines and a white noise generator.