3 resultados para Small Area Estimation
em Biblioteca de Teses e Dissertações da USP
Resumo:
ALICE is one of four major experiments of particle accelerator LHC installed in the European laboratory CERN. The management committee of the LHC accelerator has just approved a program update for this experiment. Among the upgrades planned for the coming years of the ALICE experiment is to improve the resolution and tracking efficiency maintaining the excellent particles identification ability, and to increase the read-out event rate to 100 KHz. In order to achieve this, it is necessary to update the Time Projection Chamber detector (TPC) and Muon tracking (MCH) detector modifying the read-out electronics, which is not suitable for this migration. To overcome this limitation the design, fabrication and experimental test of new ASIC named SAMPA has been proposed . This ASIC will support both positive and negative polarities, with 32 channels per chip and continuous data readout with smaller power consumption than the previous versions. This work aims to design, fabrication and experimental test of a readout front-end in 130nm CMOS technology with configurable polarity (positive/negative), peaking time and sensitivity. The new SAMPA ASIC can be used in both chambers (TPC and MCH). The proposed front-end is composed of a Charge Sensitive Amplifier (CSA) and a Semi-Gaussian shaper. In order to obtain an ASIC integrating 32 channels per chip, the design of the proposed front-end requires small area and low power consumption, but at the same time requires low noise. In this sense, a new Noise and PSRR (Power Supply Rejection Ratio) improvement technique for the CSA design without power and area impact is proposed in this work. The analysis and equations of the proposed circuit are presented which were verified by electrical simulations and experimental test of a produced chip with 5 channels of the designed front-end. The measured equivalent noise charge was <550e for 30mV/fC of sensitivity at a input capacitance of 18.5pF. The total core area of the front-end was 2300?m × 150?m, and the measured total power consumption was 9.1mW per channel.
Resumo:
ALICE is one of four major experiments of particle accelerator LHC installed in the European laboratory CERN. The management committee of the LHC accelerator has just approved a program update for this experiment. Among the upgrades planned for the coming years of the ALICE experiment is to improve the resolution and tracking efficiency maintaining the excellent particles identification ability, and to increase the read-out event rate to 100 KHz. In order to achieve this, it is necessary to update the Time Projection Chamber detector (TPC) and Muon tracking (MCH) detector modifying the read-out electronics, which is not suitable for this migration. To overcome this limitation the design, fabrication and experimental test of new ASIC named SAMPA has been proposed . This ASIC will support both positive and negative polarities, with 32 channels per chip and continuous data readout with smaller power consumption than the previous versions. This work aims to design, fabrication and experimental test of a readout front-end in 130nm CMOS technology with configurable polarity (positive/negative), peaking time and sensitivity. The new SAMPA ASIC can be used in both chambers (TPC and MCH). The proposed front-end is composed of a Charge Sensitive Amplifier (CSA) and a Semi-Gaussian shaper. In order to obtain an ASIC integrating 32 channels per chip, the design of the proposed front-end requires small area and low power consumption, but at the same time requires low noise. In this sense, a new Noise and PSRR (Power Supply Rejection Ratio) improvement technique for the CSA design without power and area impact is proposed in this work. The analysis and equations of the proposed circuit are presented which were verified by electrical simulations and experimental test of a produced chip with 5 channels of the designed front-end. The measured equivalent noise charge was <550e for 30mV/fC of sensitivity at a input capacitance of 18.5pF. The total core area of the front-end was 2300?m × 150?m, and the measured total power consumption was 9.1mW per channel.
Resumo:
We evaluate the use of Generalized Empirical Likelihood (GEL) estimators in portfolios efficiency tests for asset pricing models in the presence of conditional information. Estimators from GEL family presents some optimal statistical properties, such as robustness to misspecification and better properties in finite samples. Unlike GMM, the bias for GEL estimators do not increase as more moment conditions are included, which is expected in conditional efficiency analysis. We found some evidences that estimators from GEL class really performs differently in small samples, where efficiency tests using GEL generate lower estimates compared to tests using the standard approach with GMM. With Monte Carlo experiments we see that GEL has better performance when distortions are present in data, especially under heavy tails and Gaussian shocks.