Computer Engineering Commons^™

Local Learning Algorithms For Stochastic Spiking Neural Networks, Bleema Rosenfeld

Dissertations

This dissertation focuses on the development of machine learning algorithms for spiking neural networks, with an emphasis on local three-factor learning rules that are in keeping with the constraints imposed by current neuromorphic hardware. Spiking neural networks (SNNs) are an alternative to artificial neural networks (ANNs) that follow a similar graphical structure but use a processing paradigm more closely modeled after the biological brain in an effort to harness its low power processing capability. SNNs use an event based processing scheme which leads to significant power savings when implemented in dedicated neuromorphic hardware such as Intel’s Loihi chip.

This work …

System Design And Performance Analysis Of Asymmetrically And Symmetrically Clipped Optical (Asco)-Ofdm For Im/Dd Optical Wireless Communications, Nan Wu

Dissertations

As the quantity of mobile communication devices, such as cellphones, tablets, and laptops, dramatically increase, the demand for high speed wireless service has been growing. Optical wireless communications (OWCs), which offer unlimited transmission bandwidth, have received a lot of attention and been studied in recent decades. They can be an effective alternative to radio frequency communications (RFCs) for indoor high speed data transmission. Intensity modulation direct detection (IM/DD) is a simple way to realize the transmission of optical wireless signals in an indoor environment. Information data streams are modulated into the intensity of optical carriers and transmitted by light emitting …