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Computer Engineering Commons

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Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

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CMOS

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Full-Text Articles in Computer Engineering

A Low-Power, Low-Area 10-Bit Sar Adc With Length-Based Capacitive Dac, Zhili Pan Dec 2022

A Low-Power, Low-Area 10-Bit Sar Adc With Length-Based Capacitive Dac, Zhili Pan

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

A 2.5 V single-ended 10-bit successive-approximation-register analog-to-digital converter (SAR ADC) based on the TSMC 65 nm CMOS process is designed with the goal of achieving low power consumption (33.63 pJ/sample) and small area (2874 µm^2 ). It utilizes a novel length-based capacitive digital-to-analog converter (CDAC) layout to achieve low total capacitance for power efficiency, and a custom static asynchronous logic to free the dependence on a high-frequency external clock source. Two test chips have been designed and the problems found through testing the first chip are analyzed. Multiple improved versions of the ADC with minor variations are implemented on the …


Cmos Radioactive Isotope Identification With Multichannel Analyzer And Embedded Neural Network, Samuel Murray Jul 2018

Cmos Radioactive Isotope Identification With Multichannel Analyzer And Embedded Neural Network, Samuel Murray

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

A radiation detection and identification system is designed and implemented to perform gamma ray spectroscopy on radioactive sources and identify which isotopes are present in the sources. A multichannel analyzer is implemented on an ASIC to process the signal produced from gamma rays detected by a scintillator and photomultiplier tube and to quantize the gamma ray energies to build a histogram. A fast, low memory embedded neural network is implemented on a microcontroller ASIC to identify the isotopes present in the gamma ray histogram produced by the multichannel analyzer in real time.

Advisors: Sina Balkir and Michael Hoffman