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Wideband Spectrum Sensing And Signal Classification For Autonomous Self-Learning Cognitive Radios, Mario Bkassiny
Wideband Spectrum Sensing And Signal Classification For Autonomous Self-Learning Cognitive Radios, Mario Bkassiny
Electrical and Computer Engineering ETDs
In this dissertation, we develop a novel cognitive radio (CR) architecture, referred to as the Radiobot [1], whose goals go beyond dynamic spectrum access (DSA) to achieve the main features of cognition, notably, self-learning and self-reconfiguration. The proposed CR architecture is based on a sequence of signal processing and machine learning techniques that enable the Radiobot to sense a wide frequency band and act autonomously by learning from past experience. To achieve its goals, the proposed CR is equipped with the following functionalities: 1) Wideband spectrum sensing, 2) non-parametric signal classification, 3) unsupervised learning and reasoning and 4) decentralized decision-making. …
Proxy-Based Acceleration For Combinatorial Optimization Problems, Benjamin Yackley
Proxy-Based Acceleration For Combinatorial Optimization Problems, Benjamin Yackley
Computer Science ETDs
Combinatorial optimization problems occur in a wide range of domains, from Bayesian network structure search to questions in neuroscience and biochemistry. However, all of these problems have in common the need to optimize some score, and often the calculation of this score is a significant source of slowness in the search for a solution. Through the use of a carefully calibrated approximation, however, this time can be significantly reduced with little effect on the quality of the results. I demonstrate here how such a proxy function can be used, as well as explore situations where the proxy strategy fails and …
Wideband Autonomous Cognitive Radios: Spectrum Awareness And Phy/Mac Decision Making, Yang Li
Wideband Autonomous Cognitive Radios: Spectrum Awareness And Phy/Mac Decision Making, Yang Li
Electrical and Computer Engineering ETDs
The cognitive radios (CRs) have opened up new ways of better utilizing the scarce wireless spectrum resources. The CRs have been made feasible by recent advances in software-defined radios (SDRs), smart antennas, reconfigurable radio frequency (RF) front-ends, and full-duplex RF front-end architectures, to name a few. Generally, a CR is considered as a dynamically reconfigurable radio capable of adapting its operating parameters to the surrounding environment. Recent developments in spectrum policy and regulatory domains also allow more flexible and efficient utilization of wider RF spectrum range in the future. In line with the future directions of CRs, a new vision …
Application Of Multiple Kernel Learning On Brain Imaging For Mental Illness Characterization, Eduardo Jose Castro Witting
Application Of Multiple Kernel Learning On Brain Imaging For Mental Illness Characterization, Eduardo Jose Castro Witting
Electrical and Computer Engineering ETDs
Mental disorders are diagnosed on the basis of reported symptoms and externally observed clinical signs. Nonetheless, these cannot be evaluated by means of clinical tests. This is the case for schizophrenia, a complex disease characterized by perturbations in language, perception, thinking, social relationships and will that affects about 1% of the U.S. population. Besides the absence of an objective assessment of symptoms to diagnose schizophrenia, not even a set of symptoms that uniquely characterize this disorder have been found. Given the absence of a biologically-based diagnosis of schizophrenia, several studies have used different brain imaging techniques in an attempt to …