T–S fuzzy‐based multi‐LAE approach for sensor linearisation

Kannan, Srinivasan

doi:10.1049/iet-smt.2018.5228

Cited by 7 publications

(1 citation statement)

References 17 publications

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“…Programmable analog circuits provide both the capability to linearize the sensor output response and to standardize it by adjusting the conditioning circuit characteristic when operation conditions change due to aging, cross-sensitivity, or sensor replacement [1,2,3,4,5,6,7,8]. The use of analog electronics allows for a reduction of the requirements of the ADC in terms of resolution, because the signal is already linearized after the correction process (note that if the input signal to the ADC is non-linear, a higher resolution is required to digitize the non-linear parts).…”

Section: Introductionmentioning

confidence: 99%

High-Level Modeling and Simulation Tool for Sensor Conditioning Circuit Based on Artificial Neural Networks

Martínez-Nieto

Marques

Sanz-Pascual

et al. 2019

Sensors

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For current microelectronic integrated systems, the design methodology involves different steps that end up in the full system simulation by means of electrical and physical models prior to its manufacture. However, the higher the circuit complexity, the more time is required to complete these simulations, jeopardizing the convergence of the numerical methods and, hence, meaning that the reliability of the results are not guaranteed. This paper shows the use of a high-level tool based on Matlab to simulate the operation of an artificial neural network implemented in a mixed analog-digital CMOS process, intended for sensor calibration purposes. The proposed standard tool enables modification of the neural model architecture to adapt its characteristics to those of the electronic system, resulting in accurate behavioral models that predict the complete microelectronic IC system behavior under different operation conditions before its physical implementation with a simple, time-efficient, and reliable solution.

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