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Designing a sigma-delta modulator using passive integrators and calibration

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Detalhes bibliográficos
Resumo:An Analog to Digital Converter (ADC) serves as vital components bridging the analog and digital domains,facilitating the conversion of real-world data into digital format. Due to its essential role across various applications, the ADC is extensively researched in electronics. Ensuring their performance remains aligned with the ever-evolving technological landscape is crucial. To achieve this, optimization algorithms are employed to enhance architectural efficiency. This study explores the potential of a passive 2-1 Multi-stAge noise SHaping (MASH) Sigma-Delta Modulator (ΣΔM) architecture as presented in[2], complemented by calibration techniques detailed in [3]. Although the architecture [2] has previously undergone optimization,calibration has not been used. The introduction of calibration methods has the potential to improve performance. To tackle this issue, a genetic algorithm was implemented using the pre-existing MATLAB® code with modifications. Additionally, a C++ code was developed to enhance speed, enabling a more thorough analysis. The primary objective was to enhance the 2-1 MASH ΣΔM while minimizing Signal-to-Noise-and-Distortion Ratio (SNDR) degradation in the presence of process variations. Monte Carlo simulations were conducted to validate performance improvements. This thesis proposes a redesigned 2-1 MASH ΣΔM based on [3].
Autores principais:Martins, Diogo Filipe da Cruz
Assunto:Analog to Digital Converter (ADC) Sigma-Delta Modulator (ΣΔM) 2-1MASH ΣΔM Calibration Genetic Algorithm
Ano:2023
País:Portugal
Tipo de documento:dissertação de mestrado
Tipo de acesso:acesso aberto
Instituição associada:Universidade Nova de Lisboa
Idioma:inglês
Origem:Repositório Institucional da UNL
Descrição
Resumo:An Analog to Digital Converter (ADC) serves as vital components bridging the analog and digital domains,facilitating the conversion of real-world data into digital format. Due to its essential role across various applications, the ADC is extensively researched in electronics. Ensuring their performance remains aligned with the ever-evolving technological landscape is crucial. To achieve this, optimization algorithms are employed to enhance architectural efficiency. This study explores the potential of a passive 2-1 Multi-stAge noise SHaping (MASH) Sigma-Delta Modulator (ΣΔM) architecture as presented in[2], complemented by calibration techniques detailed in [3]. Although the architecture [2] has previously undergone optimization,calibration has not been used. The introduction of calibration methods has the potential to improve performance. To tackle this issue, a genetic algorithm was implemented using the pre-existing MATLAB® code with modifications. Additionally, a C++ code was developed to enhance speed, enabling a more thorough analysis. The primary objective was to enhance the 2-1 MASH ΣΔM while minimizing Signal-to-Noise-and-Distortion Ratio (SNDR) degradation in the presence of process variations. Monte Carlo simulations were conducted to validate performance improvements. This thesis proposes a redesigned 2-1 MASH ΣΔM based on [3].