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Sadahiro TANI Toshimasa MATSUOKA Yusaku HIRAI Toshifumi KURATA Keiji TATSUMI Tomohiro ASANO Masayuki UEDA Takatsugu KAMATA
In the present paper, we propose a novel high-resolution analog-to-digital converter (ADC) for low-power biomedical analog front-ends, which we call the successive stochastic approximation ADC. The proposed ADC uses a stochastic flash ADC (SF-ADC) to realize a digitally controlled variable-threshold comparator in a successive-approximation-register ADC (SAR-ADC), which can correct errors originating from the internal digital-to-analog converter in the SAR-ADC. For the residual error after SAR-ADC operation, which can be smaller than thermal noise, the SF-ADC uses the statistical characteristics of noise to achieve high resolution. The SF-ADC output for the residual signal is combined with the SAR-ADC output to obtain high-precision output data using the supervised machine learning method.
Sadahiro TANI Yoshihiro UCHIDA Makoto FURUIE Shuji TSUKIYAMA BuYeol LEE Shuji NISHI Yasushi KUBOTA Isao SHIRAKAWA Shigeki IMAI
The problem of calculating parasitic capacitances between two interconnects is investigated dedicatedly for liquid crystal displays, with the main focus put on the approximate expressions of the capacitances caused at the intersection and the parallel running of two interconnects. To derive simple and accurate approximate expressions, the interconnects in these structures are divided into a few basic coupling regions in such a way that the electro-magnetic field in each region can be calculated by a 2-D capacitance model. Then the capacitance in such a region is represented by a simple expression adjusted to the results computed by an electro-magnetic field solver. The total capacitance obtained by summing the capacitances in all regions is evaluated in comparison with the one obtained by using a 3-D field solver, resulting in a relative error of less than 5%.