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Perumal, SubramoniamStability and Switchability in Recurrent Neural Networks
MS, University of Cincinnati, 2008, Engineering : Computer Science

Artificial Neural Networks (ANNs) are being extensively researched for their wide range of applications. Among the most important is the ability of a type of ANNs—recurrent attractor networks—to work as associative memories. The most common type of ANN used for associative memory is the Hopfield network, which is a fully connected network with symmetric connections. There have been numerous attempts to improve the capacity and recall quality of recurrent networks, with the focus primarily on the stability of the stored attractors, and the network's convergence properties. However, the ability of a recurrent attractor network to switch between attractors is also an interesting property, if it can be harnessed for use. Such switching can be useful as a model of switching between context-dependent functional networks thought to underlie cognitive processing.

In this thesis, we design and develop a stable-yet-switchable (SyS) network model which provides an interesting combination of stability and switchability. The network is stable under random perturbations, but highly sensitive to specific targeted perturbations which cause it to switch attractors. Such functionality has previously been reported in networks with scale-free (SF) connectivity. We introduce networks with two regions: A densely connected core region, and a sparsely connected and larger periphery. We show that these core-periphery (CP) networks are better for providing a combination of stability and targeted switching than scale-free networks. We develop and validate a specific approach to switching between attractors in a targeted way. The CP and SF models are also compared with each other and with randomly connected homogeneous networks.

Committee:

Dr. Ali Minai (Advisor); Dr. Raj Bhatnagar (Committee Member); Dr. Anca Ralescu (Committee Member)

Subjects:

Computer Science; Engineering

Keywords:

recurrent neural networks; core-periphery networks; switchability; switching between attractors; stability and switchability

Kilaru, Murali KrishnaElectrowetting Switchable Retroreflectors
PhD, University of Cincinnati, 2010, Engineering and Applied Science: Electrical Engineering

Corner cube and spherical retroreflectors are ubiquitous in conspicuity and range-finding applications since they reflect light back to the illumination source with unmatched efficiency. A majority of these retroreflector applications are naked-eye applications meaning they are used in the visible spectrum for applications such as road markers, signage, safety markers, friend-foe identification, ranging. Other applications include free-space communications. More recently, switchable retroreflection has been realized through electro-mechanics or multiple quantum wells for free-space communications. However, lack of scalability, complex fabrication and limited spectrum present challenges if these devices are to be used in naked-eye applications.

Electrowetting has demonstrated robust beam steering, lenses, displays, and lab on chip devices with simple and scalable fabrication techniques. Electrowetting is voltage manipulation of wetting of polar liquids on a dielectric surface. It is envisioned that the same effect can be used to modulate retroreflection from corner cubes by means of an optical lenslet. In this dissertation we present a novel switchable retroreflector platform based on electrowetting that can potentially be a suitable candidate for naked-eye applications.

Presented in this dissertation is the world’s first simple, scalable, inexpensive, high contrast, low power and wide view angle electrowetting retroreflector for visible spectrum applications. Preliminary understanding of the electrowetting retroreflector is presented by means of simple theoretical models. Experimental investigation of contrast ratio, view angle, switching speeds and power consumption is undertaken in view of addressing the needs of naked eye applications. The achieved results clearly promote it as a good choice for the switchable retroreflector platform in visible and infra-red spectrum applications.

Committee:

Jason Heikenfeld, PhD (Committee Chair); Joseph Thomas Boyd, PhD (Committee Member); Peter Kosel, PhD (Committee Member); Fred Beyette, PhD (Committee Member); Donglu Shi, PhD (Committee Member)

Subjects:

Electrical Engineering

Keywords:

Electrowetting;Retroreflectors;Switchability;high contrast;wide spectrum;Corner cubes