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Now showing items 141-148 of 148
Throughput Maximization for Full Duplex Wireless Powered Communication Networks
(Institute of Electrical and Electronics Engineers Inc., 2020)
In this paper, we consider a full duplex wireless powered communication network where multiple users with RF energy harvesting capabilities communicate to a hybrid energy and information access point. An optimization ...
A Novel Transmit Array Structure for Optical Spatial Modulation
(IEEE, 2019)
The performance of multiple input single output (MISO) and multiple input multiple output (MIMO) systems is limited by spatial channel correlation. This limitation becomes particularly severe in light lidelity (LiFi) ...
Broadband Matching via Reflection Coefficient Modeling
(AVES YAYINCILIK, 2016)
[Abstract Not Available]
Frustrated Potts model: Multiplicity eliminates chaos via reentrance
(Amer Physical Soc, 2020)
The frustrated q-state Potts model is solved exactly on a hierarchical lattice, yielding chaos under rescaling, namely, the signature of a spin-glass phase, as previously seen for the Ising (q = 2) model. However, the ...
A Hybrid Deep Learning Framework for Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Data
(Mdpi, 2020)
Multivariate time-series data with a contextual spatial attribute have extensive use for finding anomalous patterns in a wide variety of application domains such as earth science, hurricane tracking, fraud, and disease ...
Throughput maximization in discrete rate based full duplex wireless powered communication networks
(John Wıley & Sons Ltd, 2020)
In this study, we consider a discrete rate full-duplex wireless powered communication network. We characterize a novel optimization framework for sum throughput maximization to determine the rate adaptation and transmission ...
Across dimensions: Two- and three-dimensional phase transitions from the iterative renormalization-group theory of chains
(2020)
Sharp two- and three-dimensional phase transitional magnetization curves are obtained by an iterative renormalization-group coupling of Ising chains, which are solved exactly. The chains by themselves do not have a phase ...
Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Data Using Deep Learning: Early Detection of COVID-19 Outbreak in Italy
(Ieee-Inst Electrıcal Electronıcs Engıneers Inc, 2020)
Unsupervised anomaly detection for spatio-temporal data has extensive use in a wide variety of applications such as earth science, traffic monitoring, fraud and disease outbreak detection. Most real-world time series data ...