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Articles 1 - 6 of 6
Full-Text Articles in Physical Sciences and Mathematics
Bio-Inspired Learning And Hardware Acceleration With Emerging Memories, Shruti R. Kulkarni
Bio-Inspired Learning And Hardware Acceleration With Emerging Memories, Shruti R. Kulkarni
Dissertations
Machine Learning has permeated many aspects of engineering, ranging from the Internet of Things (IoT) applications to big data analytics. While computing resources available to implement these algorithms have become more powerful, both in terms of the complexity of problems that can be solved and the overall computing speed, the huge energy costs involved remains a significant challenge. The human brain, which has evolved over millions of years, is widely accepted as the most efficient control and cognitive processing platform. Neuro-biological studies have established that information processing in the human brain relies on impulse like signals emitted by neurons called …
Blind Separation For Intermittent Sources Via Sparse Dictionary Learning, Annan Dong
Blind Separation For Intermittent Sources Via Sparse Dictionary Learning, Annan Dong
Dissertations
Radio frequency sources are observed at a fusion center via sensor measurements made over slow flat-fading channels. The number of sources may be larger than the number of sensors, but their activity is sparse and intermittent with bursty transmission patterns. To account for this, sources are modeled as hidden Markov models with known or unknown parameters. The problem of blind source estimation in the absence of channel state information is tackled via a novel algorithm, consisting of a dictionary learning (DL) stage and a per-source stochastic filtering (PSF) stage. The two stages work in tandem, with the latter operating on …
Probabilistic Spiking Neural Networks : Supervised, Unsupervised And Adversarial Trainings, Alireza Bagheri
Probabilistic Spiking Neural Networks : Supervised, Unsupervised And Adversarial Trainings, Alireza Bagheri
Dissertations
Spiking Neural Networks (SNNs), or third-generation neural networks, are networks of computation units, called neurons, in which each neuron with internal analogue dynamics receives as input and produces as output spiking, that is, binary sparse, signals. In contrast, second-generation neural networks, termed as Artificial Neural Networks (ANNs), rely on simple static non-linear neurons that are known to be energy-intensive, hindering their implementations on energy-limited processors such as mobile devices. The sparse event-based characteristics of SNNs for information transmission and encoding have made them more feasible for highly energy-efficient neuromorphic computing architectures. The most existing training algorithms for SNNs are based …
Supercapacitors With Gate Electrodes, Tazima Selim Chowdhury
Supercapacitors With Gate Electrodes, Tazima Selim Chowdhury
Dissertations
A new approach to improve the capacitance of supercapacitors (SC) is proposed in this study. A typical SC is composed of an anode and a cathode; a separator in between them assures an unintentional discharge of the capacitor. The study focuses on a family of structured separators, either electronically active or passive which are called gates. An active structured separator layer has been fabricated and analyzed. The structured separator has characteristics of electrical diode and is fabricated out of functionalized carbon nanotubes (CNT). Improvement of the overall capacitance of SC, equipped with either active or passive structured separators demonstrated a …
Surface-Enhanced Raman Detection Of Glucose On Several Novel Substrates For Biosensing Applications, Laila Saad Alqarni
Surface-Enhanced Raman Detection Of Glucose On Several Novel Substrates For Biosensing Applications, Laila Saad Alqarni
Dissertations
The small normal Raman cross-section of glucose is considered to be a major challenge for its detection by Surface Enhanced Raman Spectroscopy (SERS) for medical applications. These applications include blood glucose level monitoring of diabetic patients and evaluation of patients with other medical conditions, since glucose is a marker for many human diseases. This dissertation focuses on Surface-Enhanced Raman Scattering primarily for the detection of glucose. Some experiments also are carried out for the detection of the corresponding enzyme glucose oxidase that is used in electrochemical glucose sensors and in biofuel cells. This project explores the possibility of utilizing Surface …
Workload Allocation In Mobile Edge Computing Empowered Internet Of Things, Qiang Fan
Workload Allocation In Mobile Edge Computing Empowered Internet Of Things, Qiang Fan
Dissertations
In the past few years, a tremendous number of smart devices and objects, such as smart phones, wearable devices, industrial and utility components, are equipped with sensors to sense the real-time physical information from the environment. Hence, Internet of Things (IoT) is introduced, where various smart devices are connected with each other via the internet and empowered with data analytics. Owing to the high volume and fast velocity of data streams generated by IoT devices, the cloud that can provision flexible and efficient computing resources is employed as a smart "brain" to process and store the big data generated from …