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Design of low-pass ladder networks with mixed lumped and distributed elements by means of artificial neural networks
(AVES YAYINCILIK, 2003)
In this paper, calculation of parameters of low-pass ladder networks with mixed lumped and
distributed elements by means of artificial neural networks is given. The results of ANN are
compared with the values that are ...
Synthesis of lossless ladder networks with simple lumped elements connected via commensurate transmission lines
(AVES YAYINCILIK, 2010)
An algorithm has been proposed, to synthesize low-pass, high-pass, band-pass and band-stop lossless ladder
networks with simple lumped elements connected via commensurate transmission lines (Unit elements, UEs). First, ...
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 ...
Physical-Layer Security With Optical Generalized Space Shift Keying
(Ieee-Inst Electrıcal Electronıcs Engıneers Inc, 2020)
Spatial modulation (SM) is a promising technique that reduces inter-channel interference while providing high power efficiency and detection simplicity. In order to ensure the secrecy of SM, precoding and friendly jamming ...
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 ...