Journal
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
Volume 15, Issue 2, Pages 716-721Publisher
INST CONTROL ROBOTICS & SYSTEMS, KOREAN INST ELECTRICAL ENGINEERS
DOI: 10.1007/s12555-015-0343-1
Keywords
Binary signals; MEMS; parameter estimation; system identification
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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.
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