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ECOLE SUPÉRIEURE D'ÉLECTRICITÉ Une grande école d'ingénieurs au cœur des sciences de l'information,de l'énergie et des systèmes |
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Journal articles
Convergence Analysis of an online Approach to Parameter Estimation Problems Based on Binary Observations
Abstract : In this paper, we present an online identification method to the problem of parameter estimation from binary observations. A recursive identification algorithm with low-storage requirements and computational complexity is derived. We prove the convergence of this method provided that the input signal satisfies a strong mixing property. Some simulation results are then given in order to illustrate the properties of this method under various scenarios. This method is appealing in the context of micro-electronic devices since it only requires a 1-bit analog-to-digital converter, with low power consumption and minimal silicon area.
Cited literature [18 references]
https://hal-supelec.archives-ouvertes.fr/hal-00747809
Contributor : Alexandra Siebert Connect in order to contact the contributor
Submitted on : Friday, November 2, 2012 - 10:17:40 AM
Last modification on : Tuesday, October 5, 2021 - 11:12:05 AM
Long-term archiving on: : Sunday, February 3, 2013 - 3:36:07 AM
Contributor : Alexandra Siebert Connect in order to contact the contributor
Submitted on : Friday, November 2, 2012 - 10:17:40 AM
Last modification on : Tuesday, October 5, 2021 - 11:12:05 AM
Long-term archiving on: : Sunday, February 3, 2013 - 3:36:07 AM
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