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A Parameter Estimation Approach based on Binary Measurements using Maximum Likelihood Analysis - Application To MEMS

Kian Jafari
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."

Keyword : Binary signals, MEMS, parameter estimation, system identification.

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