Dynamic Control Modelling of a Bipole Converter Station in a Multi-terminal HVDC Grid

Barrera-Singaña, Carlos; Valenzuela, Alex; Comech, M.P.

doi:10.1109/inciscos.2017.45

Cited by 4 publications

(5 citation statements)

References 19 publications

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“…Holding the Z as constant, we can find the minimum value of the function on w and b in closed form. To find the coefficients in this way, the ELM methodology is used as an algorithm for retrieving hidden variables through the solution of a convex program [ 21 , 25 ].…”

Section: Methodsmentioning

confidence: 99%

Machine Learning Methods to Detect Voltage Glitch Attacks on IoT/IIoT Infrastructures

Jiang

2022

Computational Intelligence and Neuroscience

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A majority of modern IoT/IIoT digital systems rely on cryptographic implementations to provide satisfactory levels of security. Hardware attacks such as side-channel analysis attacks or fault injection attacks can significantly degrade and even eliminate the desired level of security of the infrastructure in question. One of the most dangerous attacks of this type is voltage glitch attacks (VGAs), which can change the intended behavior of a system. By effectively manipulating the voltage at a specific time, an error can be injected that can change the intentional conduct and bypass system security features or even extract confidential information such as encryption keys by analyzing incorrect outputs of the firmware. This study proposes an innovative VGAs detection system based on advanced machine learning. Specifically, an innovative semisupervised learning methodology is used that utilizes a hybrid combination of algorithms. Specifically, a heuristic clustering method is used based on a linear fragmentation of group classes. In contrast, the ELM methodology is used as an algorithm for retrieving hidden variables through convex optimization.

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Section: Methodsmentioning

confidence: 99%

Machine Learning Methods to Detect Voltage Glitch Attacks on IoT/IIoT Infrastructures

Jiang

2022

Computational Intelligence and Neuroscience

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“…Based on what was previously mentioned, for high intensity of the electric field (e.g. for Ε>10 5 V/cm) where the presence of non-linear phenomena becomes significant, in the equation describing the polarization conditions of higher rate appear and the polarization is presented as an expansion of the Taylor sequence according to the following form [33], [35]:…”

Section: Nature Of Lightmentioning

confidence: 99%

“…As far as the procedure that causes the appearance of a non-linear optic behavior is concerned, when some radiation impacts on some material, it causes changes in the spatial and temporal distribution of the electric charge, inducing electric bipoles, the macroscopic result of which is the creation or modification of the polarization of the material [33]. For low values of the E field, the P polarization is analogous to the E field that caused it and the elementary bipoles, when oscillated, emit radiation of the same properties as the impacting radiation.…”

Section: Nature Of Lightmentioning

confidence: 99%

A Comprehensive Survey on Nanophotonics Neural Networks

Demertzis¹,

Παπαδόπουλος²,

Iliadis³

et al. 2021

Preprint

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: In the last years, materializations of neuromorphic circuits based on nanophotonic arrangements have been proposed, which contain complete optical circuits, laser, photodetectors, photonic crystals, optical fibers, flat waveguides, and other passive optical elements of nanostructured materials, which eliminate the time of simultaneous processing of big groups of data, taking advantage of the quantum perspective and thus highly increasing the potentials of contemporary intelligent computational systems. This article is an effort to record and study the research that has been conducted concerning the methods of development and materialization of neuromorphic circuits of Neural Networks of nanophotonic arrangements. In particular, an investigative study of the methods of developing nanophotonic neuromorphic processors, their originality in neuronic architectural structure, their training methods and their optimization has been realized along with the study of special issues such as optical activation functions and cost functions.

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“…As far as the procedure that causes the appearance of a non-linear optic behavior is concerned, when some radiation impacts on some material, it causes changes in the spatial and temporal distribution of the electric charge, inducing electric dipoles, the macroscopic result of which is the creation or modification of the polarization of the material [ 33 ]. For low values of the E field, the P polarization is analogous to the E field that caused it and the elementary dipoles, when oscillated, emit radiation of the same properties as the impacting radiation.…”

Section: Nature Of Lightmentioning

confidence: 99%

“…Based on what was previously mentioned, for high intensity of the electric field (e.g., for Ε > 10 5 V/cm) where the presence of non-linear phenomena becomes significant, in the equation describing the polarization conditions of a higher rate appear, and the polarization is presented as an expansion of the Taylor sequence according to the following form [ 33 , 35 ]:

where

is the second-rate susceptibility,

is the third-rate susceptibility and so on and so forth. The susceptibilities are generally tensors, so, for instance, the first-rate susceptibility

is a second-rate tensor with 3 × 3 = 9 elements and the corresponding polarization is presented by the following form [ 25 , 34 , 35 ]:

where

.…”

Section: Nature Of Lightmentioning

confidence: 99%

A Comprehensive Survey on Nanophotonic Neural Networks: Architectures, Training Methods, Optimization, and Activations Functions

Demertzis

Papadopoulos

Iliadis

et al. 2022

Sensors

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In the last years, materializations of neuromorphic circuits based on nanophotonic arrangements have been proposed, which contain complete optical circuits, laser, photodetectors, photonic crystals, optical fibers, flat waveguides and other passive optical elements of nanostructured materials, which eliminate the time of simultaneous processing of big groups of data, taking advantage of the quantum perspective, and thus highly increasing the potentials of contemporary intelligent computational systems. This article is an effort to record and study the research that has been conducted concerning the methods of development and materialization of neuromorphic circuits of neural networks of nanophotonic arrangements. In particular, an investigative study of the methods of developing nanophotonic neuromorphic processors, their originality in neuronic architectural structure, their training methods and their optimization was realized along with the study of special issues such as optical activation functions and cost functions. The main contribution of this research work is that it is the first time in the literature that the most well-known architectures, training methods, optimization and activations functions of the nanophotonic networks are presented in a single paper. This study also includes an extensive detailed meta-review analysis of the advantages and disadvantages of nanophotonic networks.

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Dynamic Control Modelling of a Bipole Converter Station in a Multi-terminal HVDC Grid

Cited by 4 publications

References 19 publications

Machine Learning Methods to Detect Voltage Glitch Attacks on IoT/IIoT Infrastructures

Machine Learning Methods to Detect Voltage Glitch Attacks on IoT/IIoT Infrastructures

A Comprehensive Survey on Nanophotonics Neural Networks

A Comprehensive Survey on Nanophotonic Neural Networks: Architectures, Training Methods, Optimization, and Activations Functions

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