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Articles 1 - 3 of 3
Full-Text Articles in Theory and Algorithms
Digital And Mixed Domain Hardware Reduction Algorithms And Implementations For Massive Mimo, Najath A. Mohomed
Digital And Mixed Domain Hardware Reduction Algorithms And Implementations For Massive Mimo, Najath A. Mohomed
FIU Electronic Theses and Dissertations
Emerging 5G and 6G based wireless communications systems largely rely on multiple-input-multiple-output (MIMO) systems to reduce inherently extensive path losses, facilitate high data rates, and high spatial diversity. Massive MIMO systems used in mmWave and sub-THz applications consists of hundreds perhaps thousands of antenna elements at base stations. Digital beamforming techniques provide the highest flexibility and better degrees of freedom for phased antenna arrays as compared to its analog and hybrid alternatives but has the highest hardware complexity.
Conventional digital beamformers at the receiver require a dedicated analog to digital converter (ADC) for every antenna element, leading to ADCs for …
Development Of Gaussian Learning Algorithms For Early Detection Of Alzheimer's Disease, Chen Fang
Development Of Gaussian Learning Algorithms For Early Detection Of Alzheimer's Disease, Chen Fang
FIU Electronic Theses and Dissertations
Alzheimer’s disease (AD) is the most common form of dementia affecting 10% of the population over the age of 65 and the growing costs in managing AD are estimated to be $259 billion, according to data reported in the 2017 by the Alzheimer's Association. Moreover, with cognitive decline, daily life of the affected persons and their families are severely impacted. Taking advantage of the diagnosis of AD and its prodromal stage of mild cognitive impairment (MCI), an early treatment may help patients preserve the quality of life and slow the progression of the disease, even though the underlying disease cannot …
Rigid And Non-Rigid Point-Based Medical Image Registration, Nestor Andres Parra
Rigid And Non-Rigid Point-Based Medical Image Registration, Nestor Andres Parra
FIU Electronic Theses and Dissertations
The primary goal of this dissertation is to develop point-based rigid and non-rigid image registration methods that have better accuracy than existing methods. We first present point-based PoIRe, which provides the framework for point-based global rigid registrations. It allows a choice of different search strategies including (a) branch-and-bound, (b) probabilistic hill-climbing, and (c) a novel hybrid method that takes advantage of the best characteristics of the other two methods. We use a robust similarity measure that is insensitive to noise, which is often introduced during feature extraction. We show the robustness of PoIRe using it to register images obtained with …