Skip navigation
Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01vx021h40n
Title: Closed Loop Control Systems Using Neural Learning Populations
Authors: Uttamadoss, Akshaya
Advisors: Prucnal, Paul
Department: Electrical Engineering
Class Year: 2015
Abstract: We begin by describing the photon neuron project, an effort to create a new photonic computational primitive based upon neural processing, and its potential to open new application domains. In particular, we focus on ultrafast control systems for high speed avionics. Then we discuss the strengths of Nengo, a neural simulator, which are its similarities to the physical photonic neuron implementation and its integration of control theory. Finally, we simulate basic control systems via function estimation using neural learning populations in Nengo. With these simulations, we show that artificial neural networks, like the photonic neuron, have the potential to be used in the construction of ultrafast control systems.
Extent: 14 pages
URI: http://arks.princeton.edu/ark:/88435/dsp01vx021h40n
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Electrical Engineering, 1932-2016

Files in This Item:
File SizeFormat 
PUTheses2015-Uttamadoss_Akshaya.pdf491.04 kBAdobe PDF    Request a copy


Items in Dataspace are protected by copyright, with all rights reserved, unless otherwise indicated.