This article contains a lists of documents regarding integrated circuits and wireless communication dissertations and theses. I will cite the dissertations mainly from Google Scholar using Chicago style in order to make it tidy and organized. Information regarding how to find the documents can be found here specifically for Virginia Tech. I presume other universities would also make their graduates’ dissertations publicly available for various benefits, specifically transparency.
You can click on the hyperlink of document title, which will direct you to the web page in VT’s server. When you hover mouse cursor onto the number, you can see the reference citation, at the end of the citation, there’s folder emoji, which contains the link pdf file of the document. You could also click on the number which will jumps to the bottom reference section, you could go back to the article by clicking on the return symbol shown at the end of the reference item. I tested and made sure readers who are interested in these documents are able to access off campus, as Google Scholar could crawl all the data from the website.
Neuromorphic computing
Spike processing circuit design for neuromorphic computing1
Powering Next-Generation Artificial Intelligence by Designing Three-dimensional High-Performance Neuromorphic Computing System with Memristors2
Moving Toward Intelligence: A Hybrid Neural Computing Architecture for Machine Intelligence Applications3
Spiking neural network with memristive based computing-in-memory circuits and architecture.4
FPGA Reservoir Computing Networks for Dynamic Spectrum Sensing.5
A Cost-Efficient Digital ESN Architecture on FPGA.6
Design and Optimization of Temporal Encoders using Integrate-and-Fire and Leaky Integrate-and-Fire Neurons.7
Energy efficient deep spiking recurrent neural networks: A reservoir computing-based approach.8
Two-Stage Operational Amplifier Design by Using Direct and Indirect Feedback Compensations.9
Wireless
Deep Reinforcement Learning for Next Generation Wireless Networks with Echo State Networks.10
Machine Learning-Based Receiver in Multiple Input Multiple Output Communications Systems.11
Efficient Sharing of Radio Spectrum for Wireless Networks.12
Radio Frequency Design
CMOS Receiver Design for Optical Communications over the Data-Rate of 20 Gb/s.13
Apart from the great contents, this dissertation is able to present high quality lossless graphics, including circuit schematics using LaTeX.
CMOS
High Performance RF Circuit Design: High Temperature, Ultra-Low Phase Noise, and Low Complexity.14
Scripting Tool
The following contains the script to handle the html code snippets based on reference and source file strings in order to generate the texts as well as its corresponding hyperlinks.
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import pathlib as pl, re
#read file contains name, reference and link for reference, generate a html snippet based on the template
source=pl.Path(__file__).parent.joinpath('source.txt')
contents=source.read_text(encoding='utf-8').split('\n')
for index, line in enumerate(contents):
if index%2==0:
ref=line
if ref=='':
exit()
name=re.findall(r'".*"', ref)[0].replace('"','')
elif index%2==1:
pdf=re.sub('\?.*$','',line)
link=re.sub('[^/]*$','',pdf.replace('/bitstream',''))
if index%2==1 and name!='' and ref!='' and link !='':
html=f'''<p><a href="{link}" data-type="link" data-id="{link}" target="_blank">{name}</a>__placeholder__<a href="{link}" data-type="link" data-id="{link}" target="_blank">{ref}</a> <a href="{pdf}" data-type="link" data-id="{pdf}" target="_blank">๐</a>__placeholder__</p>'''
print(html)
For example, the script reads the source.txt that contains one or multiple citation and pdf link pairs, which is located in the same directory as the script as follows.
Nowshin, Fabiha. "Spiking neural network with memristive based computing-in-memory circuits and architecture." PhD diss., Virginia Tech, 2021.
https://vtechworks.lib.vt.edu/bitstream/handle/10919/103854/Nowshin_F_T_2021.pdf?sequence=1&isAllowed=ys
After running the script, the output html can be used directory on wordpress posts. The specific forms depends on the definitions of various schools’ systems. I purposely added 2 back slashes at the brackets which should not exists to avoid triggering the citation keyword.
<p><a href="https://vtechworks.lib.vt.edu/handle/10919/103854/" data-type="link" data-id="https://vtechworks.lib.vt.edu/handle/10919/103854/" target="_blank">Spiking neural network with memristive based computing-in-memory circuits and architecture.</a>\(\(<a href="https://vtechworks.lib.vt.edu/handle/10919/103854/" data-type="link" data-id="https://vtechworks.lib.vt.edu/handle/10919/103854/" target="_blank">Nowshin, Fabiha. "Spiking neural network with memristive based computing-in-memory circuits and architecture." PhD diss., Virginia Tech, 2021.</a> <a href="https://vtechworks.lib.vt.edu/bitstream/handle/10919/103854/Nowshin_F_T_2021.pdf" data-type="link" data-id="https://vtechworks.lib.vt.edu/bitstream/handle/10919/103854/Nowshin_F_T_2021.pdf" target="_blank">๐</a>\)\)</p>
The rendered html is shown as below:
Spiking neural network with memristive based computing-in-memory circuits and architecture.4
- Zhao, Chenyuan. “Spike processing circuit design for neuromorphic computing.” PhD diss., Virginia Tech, 2019. ๐[↩]
- An, Hongyu. “Powering Next-Generation Artificial Intelligence by Designing Three-Dimensional High-Performance Neuromorphic Computing System with Memristors.” PhD diss., Virginia Tech, 2020. ๐[↩]
- Bai, Kang Jun. “Moving Toward Intelligence: A Hybrid Neural Computing Architecture for Machine Intelligence Applications.” PhD diss., Virginia Tech, 2021. ๐[↩]
- Nowshin, Fabiha. “Spiking neural network with memristive based computing-in-memory circuits and architecture.” PhD diss., Virginia Tech, 2021. ๐[↩][↩]
- Shears, Osaze Yahya. “FPGA Reservoir Computing Networks for Dynamic Spectrum Sensing.” PhD diss., Virginia Tech, 2022. ๐[↩]
- Gan, Victor Ming. “A Cost-Efficient Digital ESN Architecture on FPGA.” PhD diss., Virginia Tech, 2020. ๐[↩]
- Anderson, Juliet Graciela. “Design and Optimization of Temporal Encoders using Integrate-and-Fire and Leaky Integrate-and-Fire Neurons.” PhD diss., Virginia Tech, 2022. ๐[↩]
- Hamedani, Kian. “Energy efficient deep spiking recurrent neural networks: A reservoir computing-based approach.” PhD diss., Virginia Tech, 2020. ๐[↩]
- Zhang, Jiayuan. “Two-Stage Operational Amplifier Design by Using Direct and Indirect Feedback Compensations.” PhD diss., Virginia Tech, 2021. ๐[↩]
- Chang, Hao-Hsuan. “Deep Reinforcement Learning for Next Generation Wireless Networks with Echo State Networks.” PhD diss., Virginia Tech, 2021. ๐[↩]
- Zhou, Zhou. “Machine Learning-Based Receiver in Multiple Input Multiple Output Communications Systems.” PhD diss., Virginia Tech, 2021. ๐[↩]
- Yuan, Xu. “Efficient Sharing of Radio Spectrum for Wireless Networks.” PhD diss., Virginia Tech, 2016. ๐[↩]
- Chong, Joseph. “CMOS Receiver Design for Optical Communications over the Data-Rate of 20 Gb/s.” PhD diss., Virginia Tech, 2018. ๐[↩]
- Lohrabi Pour, Fariborz. “High Performance RF Circuit Design: High Temperature, Ultra-Low Phase Noise, and Low Complexity.” PhD diss., Virginia Tech, 2022. ๐[↩]
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