|A Parameter Estimation Approach based on Binary Measurements using Maximum Likelihood Analysis - Application To MEMS
International Journal of Control, Automation, and Systems, vol. 15, no. 2, pp.716-721, 2017
Abstract : "This paper presents an attitude towards the parameter estimation problems, based on binary output observations,
dedicated to the context of micro-electronic devices such as Micro-Electro-Mechanical Systems (MEMS)
self-testing. This approach is based on Maximum Likelihood (ML) estimation of a logistic regression model of a
Finite Impulse Response (FIR) system with binary output data. The results of the proposed method are compared
with an appropriate approach in the micro-electronic field under various scenarios, where it is competitive with the
compared one. This competition becomes bold in the case of a powerful signal-to-noise ratio (SNR) in the system."
Binary signals, MEMS, parameter estimation, system identification.
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