Impulse Response Estimation with Binary Measurements: A Regularized FIR Model
2012 (English)In: Proceedings of the 16th IFAC Symposium on System Identification, 2012, 113-118 p.Conference paper (Refereed)
FIR (finite impulse response) model is widely used in tackling the problem of the impulse response estimation with quantized measurements. Its use is, however, limited, in the case when a high order FIR model is required to capture a slowly decaying impulse response. This is because the high variance for high order FIR models would override the low bias and thus lead to large MSE (mean square error). In this contribution, we apply the recently introduced regularized FIR model approach to the problem of the impulse response estimation with binary measurements. We show by Monte Carlo simulations that the proposed approach can yield both better accuracy and better robustness than a recently introduced FIR model based approach.
Place, publisher, year, edition, pages
2012. 113-118 p.
Nonparametric methods, Bayesian methods
IdentifiersURN: urn:nbn:se:liu:diva-95603DOI: 10.3182/20120711-3-BE-2027.00219ISBN: 978-3-902823-06-9OAI: oai:DiVA.org:liu-95603DiVA: diva2:636489
16th IFAC Symposium on System Identification, Brussels, Belgium, 11-13 July, 2012