Design of a Low Temperature Drift Bandgap Reference Circuit with Second-order Curvature Compensation
Issue:
Volume 8, Issue 3, June 2020
Pages:
46-51
Received:
9 June 2020
Published:
29 June 2020
Abstract: In order to improve the accuracy and stability of bandgap reference output voltage, a bandgap reference circuit with high power supply rejection ratio and low temperature drift is designed based on 0.18um BCD technology. Based on the traditional bandgap voltage reference structure, this paper designs a current mirror cascade and a prereference circuit to supply power to the bandgap reference, and achieves a high power rejection ratio. At the same time, a PTAT2 current generation circuit is designed to realize the second-order temperature compensation of the reference output voltage. The simulation results show that the power supply voltage is 5V, PSRR is - 80dB, the temperature changes from - 55°C to 125°C, and the reference voltage temperature coefficient is 4.27ppm /°C. The circuit is simple in structure and easy to integrate. It can be widely used in bandgap reference circuit design.
Abstract: In order to improve the accuracy and stability of bandgap reference output voltage, a bandgap reference circuit with high power supply rejection ratio and low temperature drift is designed based on 0.18um BCD technology. Based on the traditional bandgap voltage reference structure, this paper designs a current mirror cascade and a prereference circ...
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Linear Regression Model of House Price in Boston
Issue:
Volume 8, Issue 3, June 2020
Pages:
52-63
Received:
23 May 2020
Published:
29 June 2020
Abstract: The change of house price is a common phenomenon. People are eager to grasp the law of house price to become the winner of real estate investment. This paper uses Boston house price data to explore the relationship between Boston house price and which independent variables. This paper uses linear regression model to construct the relationship between housing prices and crime rate in Boston. First, the classical linear model is adopted. Then we do the collinearity test, removing the lever point and other operations, the residual of the model still does not conform to the normal distribution, so the classical linear model cannot describe the data very well. Then, we add the quadratic term and the cross term, and use the method of stepwise regression to get the optimal regression autoregressive quantum set. After removing the leverage point and significance test, we found that the residual distribution was approximately normal. It shows that the improved model has well described the law of data. Finally, according to the data, the main conclusions are as follows: house price and tax rate, index close to the highway and index close to the city center are inversely correlated, which is positively correlated with the number of rooms, the proportion of teachers and students, and whether it is close to the Charles River. In addition, the concentration of nitric oxide, the proportion of low-end population and crime rate also have a certain relationship with housing prices.
Abstract: The change of house price is a common phenomenon. People are eager to grasp the law of house price to become the winner of real estate investment. This paper uses Boston house price data to explore the relationship between Boston house price and which independent variables. This paper uses linear regression model to construct the relationship betwe...
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