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Concept

Circuit RL

Publications associées (31)

Analysis of the Effectiveness of the Series Inductor Integration Into the MFT for SST Applications

Drazen Dujic, Marko Mogorovic

This paper analyzes the effectiveness of the integration of the series inductor into the medium frequency transformer used for series resonant or dual active bridge converters - galvanically isolated DC-DC converters for high-power medium-voltage (solid st ...

2020

3D Smith chart constant quality factor semi-circles contours for positive and negative resistance circuits

Mihai Adrian Ionescu, Andrei Müller

The article firstly proves that the constant quality factor (Q) contours for passive circuits, while represented on a 2D Smith chart, form circle arcs on a coaxal circle family. Furthermore, these circle arcs represent semi-circles families in the north he ...

2020

Accurate Emulation of Memristive Crossbar Arrays for In-Memory Computing

Irem Boybat Kara

In-memory computing is an emerging non-von Neumann computing paradigm where certain computational tasks are performed in memory by exploiting the physical attributes of the memory devices. Memristive devices such as phase-change memory (PCM), where informa ...

IEEE2020

Aqueous effluent treatment system

Jeremy Luterbacher, Gaël Peng, Frédéric Edouard Juillard

Aqueous effluent treatment system (2) including a separation reactor (4) having a reactor chamber fluidly connected to an aqueous effluent source (3), connected via a pump (5) to an inlet (34) of the reactor chamber, a fluid extraction system (6) connected ...

2020

Effects of 5 MeV electron irradiation on deep traps and electroluminescence from near-UV InGaN/GaN single quantum well light-emitting diodes with and without InAlN superlattice underlayer

Nicolas Grandjean, Jean-François Carlin, Raphaël Butté, Camille Haller

The electrical properties, electroluminescence (EL) power output and deep trap spectra were studied before and after 5 MeV electron irradiation of near-UV single-quantum-well (SQW) light-emitting diodes (LED) structures differing by the presence or absence ...

IOP PUBLISHING LTD2020

Output Capacitance Losses in Wide-Band-Gap Transistors: A Small-Signal Modeling Approach

Elison de Nazareth Matioli, Armin Jafari, Mohammad Samizadeh Nikooytabalvandani, Palliyage Srilak Nirmana Perera

Wide-band-gap (WBG) power semiconductor devices are gaining an increasing interest in power circuits, as they exhibit a low specific ON-resistance (RON) while providing a high blocking voltage. The energy dissipation corresponding to resonantly charging an ...

IEEE2020

Evidence of Smaller 1/F Noise in AlScN-Based Oscillators Compared to AlN-Based Oscillators

Luis Guillermo Villanueva Torrijo, Andrea Lozzi, Marco Liffredo

In this paper we investigate the direct effect of resonator quality factor (Q) on the oscillator phase noise. We use 2-port contour mode resonators (CMRs), fabricated both with aluminum nitride (AlN) and aluminum scandium nitride (AlScN), as the frequency- ...

Institute of Electrical and Electronics Engineers2020

Energy Analysis of Lightweight AEAD Circuits

Subhadeep Banik, Andrea Felice Caforio, Muhammed Fatih Balli

The selection criteria for NIST's Lightweight Crypto Standardization (LWC) have been slowly shifting towards the lightweight efficiency of designs, given that a large number of candidates already establish their security claims on conservative, well-studie ...

2020

Buffer Placement and Sizing for High-Performance Dataflow Circuits

Paolo Ienne, Andrea Guerrieri, Lana Josipovic

Commercial high-level synthesis tools typically produce statically scheduled circuits. Yet, effective C-to-circuit conversion of arbitrary software applications calls for dataflow circuits, as they can handle efficiently variable latencies (e.g., caches) a ...

ASSOC COMPUTING MACHINERY2020

Data driven building of realistic neuron model using IBEA and CMA evolution strategies

Henry Markram, Werner Alfons Hilda Van Geit, Tanguy Pierre Louis Damart

Recently the building of large neuronal circuits from realistic neuron models has gained traction. This bottom-up approach relies on the accurate description of the primitive elements composing the brain such as neurons and astrocytes, that are then aggreg ...

ACM2020

Multi-memristive synaptic architectures for training neural networks

Irem Boybat Kara

Highly data-centric AI workloads require that new computing paradigms be adopted because the performance of traditional CPU- and GPU-based systems are limited by data access and transfer. Training deep neural networks with millions of tunable parameters ta ...

EPFL2020