Design of test signals for identification of linear systems with nonlinear distortions

Evans, D.C.; Rees, D.; Jones, David Lee

doi:10.1109/19.199395

Cited by 24 publications

(3 citation statements)

References 11 publications

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“…Recall the Volterra expansion of H (10) and set the k th input to v (k) t , the k th order DPSS for k ≤ K. Here, K is chosen such that v (k) t , k ≤ K possesses energy concentration within (−W, W ) near one. From (8), this is equivalent to specifying that the first K DPSS eigenvalues, λ k , are as close to 1 as possible. Thus, of all DPSSs index-limited to the interval [0, N − 1] with a given time-bandwidth parameter N W , these sequences are the most energy concentrated DPSSs within the frequency interval (−W, W ).…”

Section: Suppression Of Higher-order Mimo Response To Dpss Inputmentioning

confidence: 99%

“…In this work, motivated by the identification of linear narrowband response, emphasis is placed upon characterizing Volterra MIMO response to DPSS input. In [8]- [10] models are considered where the higher-order nonlinear system response is small and additive. This differs from the proposed work in that (i) sinusoidal input with random phases are used as opposed to the optimal in-band energy concentrated DPSSs and (ii) the nonlinear system response in the proposed work is suppressed by the use of DPSS as input.…”

Section: Table I Key Parametersmentioning

confidence: 99%

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On the Output of Nonlinear Systems Excited by Discrete Prolate Spheroidal Sequences

Lepage

Ching

2017

IEEE Trans. Automat. Contr.

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The discrete prolate spheroidal sequences (DPSSs) -a set of optimally bandlimited sequences with unique properties -are important to applications in both science and engineering. In this work, properties of nonlinear system response due to DPSS excitation are reported. In particular, this output is shown to be approximately orthogonal after passing through a nonlinear, multiple-input multiple-output system with memory under quite general conditions. This work quantifies these conditions in terms of constraints upon the higher-order generalized transfer functions characterizing the Volterra expansion of a MIMO system, the Volterra order of the system, and the DPSS bandwidth parameter W and time-bandwidth parameter N W . The approximate system output orthogonality allows multiple-input, multiple-output parameter identification of edge structure in interconnected nonlinear systems using simultaneous, DPSS excitation. This narrowband method of system identification is particularly appealing when compared to classical broadband system excitation in sensitive, neural engineering applications involving electrical stimulation of multiple brain regions. Through the comparison of inner-product and kernel-based narrowband detectors, the utility of this work is demonstrated when identifying narrowband system response of a third-order Volterra system from noisy observations.

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Section: Suppression Of Higher-order Mimo Response To Dpss Inputmentioning

confidence: 99%

Section: Table I Key Parametersmentioning

confidence: 99%