Articles producció científica> Enginyeria Electrònica, Elèctrica i Automàtica

Noise-Based Simulation Technique for Circuit-Variability Analysis

  • Datos identificativos

    Identificador: imarina:9139053
    Handle: https://hdl.handle.net/20.500.11797/imarina9139053
    Autores:
    Nikolaou ALeise JPruefer JZschieschang UKlauk HDarbandy GIniguez BKloes A
    Resumen:
    CCBY An accurate and efficient noise-based simulation technique for predicting the impact of device-parameter variability on the DC statistical behavior of integrated circuits is presented. The proposed method is validated on a source follower, a diode-load inverter and a current mirror based on organic thin-film transistors. Taking advantage of the standard noise analysis of a circuit, after translating the statistical variation of the electrical parameters of the transistors into equivalent-noise circuit components, the proposed technique yields results identical to those obtained from a Monte Carlo simulation, but in a significantly shorter amount of time.

  • Otros:

    Autor según el artículo: Nikolaou A; Leise J; Pruefer J; Zschieschang U; Klauk H; Darbandy G; Iniguez B; Kloes A
    Departamento: Enginyeria Electrònica, Elèctrica i Automàtica
    e-ISSN: 1557-9646
    Autor/es de la URV: Iñiguez Nicolau, Benjamin
    Palabras clave: Verilog-a Variability Transistors Threshold voltage Thin-film transistors Thin-film transistor Thin film transistors Organic circuits. Organic circuits Noise Monte carlo methods Monte carlo analysis Model Logic gates Integrated circuit modeling Hardware design languages Compact modeling
    Resumen: CCBY An accurate and efficient noise-based simulation technique for predicting the impact of device-parameter variability on the DC statistical behavior of integrated circuits is presented. The proposed method is validated on a source follower, a diode-load inverter and a current mirror based on organic thin-film transistors. Taking advantage of the standard noise analysis of a circuit, after translating the statistical variation of the electrical parameters of the transistors into equivalent-noise circuit components, the proposed technique yields results identical to those obtained from a Monte Carlo simulation, but in a significantly shorter amount of time.
    Áreas temáticas: Engineering, electrical & electronic Electronic, optical and magnetic materials Electrical and electronic engineering Biotechnology
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    ISSN: 0018-9383
    Direcció de correo del autor: benjamin.iniguez@urv.cat
    Identificador del autor: 0000-0002-6504-7980
    Fecha de alta del registro: 2024-07-27
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Enlace a la fuente original: https://ieeexplore.ieee.org/document/9302569
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Ieee Journal Of The Electron Devices Society. 9 450-455
    Referencia de l'ítem segons les normes APA: Nikolaou A; Leise J; Pruefer J; Zschieschang U; Klauk H; Darbandy G; Iniguez B; Kloes A (2021). Noise-Based Simulation Technique for Circuit-Variability Analysis. Ieee Journal Of The Electron Devices Society, 9(), 450-455. DOI: 10.1109/JEDS.2020.3046301
    DOI del artículo: 10.1109/JEDS.2020.3046301
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2021
    Tipo de publicación: Journal Publications

  • Palabras clave:

    Biotechnology,Electrical and Electronic Engineering,Electronic, Optical and Magnetic Materials,Engineering, Electrical & Electronic
    Verilog-a
    Variability
    Transistors
    Threshold voltage
    Thin-film transistors
    Thin-film transistor
    Thin film transistors
    Organic circuits.
    Organic circuits
    Noise
    Monte carlo methods
    Monte carlo analysis
    Model
    Logic gates
    Integrated circuit modeling
    Hardware design languages
    Compact modeling
    Engineering, electrical & electronic
    Electronic, optical and magnetic materials
    Electrical and electronic engineering
    Biotechnology

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