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Comments on “Development of an ANN-Based Linearization Technique for the VCO Thermistor Circuit”

机译:关于“为VCO热敏电阻电路开发基于ANN的线性化技术的评论”

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摘要

Recently, Kumar et al. [1] have reported an Artificial Neural Network (ANN) based linearization technique for Voltage Controlled Oscillator (VCO) thermistor circuit. In this work ANN was used to linearize the frequency output of VCO, driven by the voltage across thermistor, for an input temperature range of 0 °C-100 °C. Performance of the developed technique was claimed to be experimentally verified for sensitivity and linearity of 5 kHz/°C and ±0.2%, respectively, for all the investigated three different thermistors (M/S Phillips make). In this comment, using the data provided in [1] and based on the relevant theoretical analysis it is shown the obtainable theoretical sensitivities are 136.918 Hz/°C, 108.919 Hz/°C and 267.938 Hz/°C for the used thermistor-1, thermistor-2 and thermistor-3, respectively, instead of the claimed 5 kHz/°C.
机译:最近,Kumar等人。 [1]已经报道了一种基于人工神经网络(ANN)的线性化技术,用于压控振荡器(VCO)热敏电阻电路。在这项工作中,对于输入温度范围为0°C-100°C,使用ANN对热敏电阻两端电压驱动的VCO频率输出进行线性化。据称,对于所有研究的三种不同的热敏电阻(M / S Phillips生产),灵敏度和线性度分别为5 kHz /°C和±0.2%时,已通过实验验证了该技术的性能。在这篇评论中,使用[1]中提供的数据并基于相关的理论分析,结果表明,对于使用的热敏电阻1,可获得的理论灵敏度为136.918 Hz /°C,108.919 Hz /°C和267.938 Hz /°C。分别为热敏电阻2和热敏电阻3,而不是要求的5 kHz /°C。

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