Characterization & Comparative Analysis of High Speed CMOS Comparator for Pipelined ADC

In todays high speed low power era, there is an increasing demand of a High Speed Comparator for ADC, DAC and various other applications in an analog and digital domain. This paper describes and analyzes five different architecture for low power and high speed comparators. In this paper, authors have analyzed and simulated the designs using TSMC 0.35 m CMOS technology with 2.0V for preamplifier based comparator and 1.8V power supply for dynamic comparators. The simulation results allow the circuit designer to fully explore the tradeoffs in comparator design, such as offset voltage, speed, power and area for Pipelined A/D Converters. Prelayout and postlayout simulations are carried out using Eldo SPICE tool and layout using IC Station

Short-Term Power Prediction of Building Integrated Photovoltaic (BIPV) System Based on Machine Learning Algorithms

One of the biggest challenges is towards ensuring large-scale integration of photovoltaic systems into buildings. This work is aimed at presenting a building integrated photovoltaic system power prediction concerning the building’s various orientations based on the machine learning data science tools. The proposed prediction methodology comprises a data quality stage, machine learning algorithm, weather clustering assessment, and an accuracy assessment. The results showed that the application of linear regression coefficients to the forecast outputs of the developed photovoltaic power generation neural network improved the PV power generation’s forecast output. The final model resulted from accurate forecasts, exhibiting a root mean square error of 4.42% in NN, 16.86% in QSVM, and 8.76% in TREE. The results are presented with the building facade and roof application such as flat roof, south façade, east façade, and west façade