Due to their numerous benefits, multi-modulation single-carrier pulse width modulation (MSC-PWM) approaches are becoming more prevalent in multilevel converter topology control systems. Compared to traditional multi-c...
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For decades, satellites have facilitated remote internet of things (IoT) services. However, the recent proliferation of increasingly capable sensors and a surge in the number deployed, has led to a substantial growth ...
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We analyze bounds to the electromagnetic local density of states achievable via material structuring, deriving novel results including finite bound saturation in the infinite susceptibility limit and sub-linear bandwi...
The Graph Laplacian Mixture Model (GLMM) allows to infer multiple underlying graph structures from multivariate time series data. Given its effectiveness in identifying brain states from brain activity measured by fun...
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The commercially available 4000-Watt continuous-wave(CW)Erbium-doped-fiber laser,emitting at the 1567-nm wavelength where the atmosphere has high transmission,provides an opportunity for harvesting electric power at r...
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The commercially available 4000-Watt continuous-wave(CW)Erbium-doped-fiber laser,emitting at the 1567-nm wavelength where the atmosphere has high transmission,provides an opportunity for harvesting electric power at remote“off the grid”locations using a multi-module photovoltaic(PV)“receiver”*** paper proposes a 32-element monocrystalline thick-layer Germanium PV panel for efficient harvesting of a collimated 1.13-m-diam *** 0.78-m^(2) PV panel is constructed from commercial Ge *** incident CW laser-beam power in the 4000 to 10,000 W range,our thermal,electrical,and infrared simulations predict 660 to 1510 Watts of electrical output at the panel temperatures of 350 to 423 K.
The wide applications of Electric Vehicles (EVs) for integration with renewable energy sources need high-power, isolated bidirectional converters (IBC). Bi-directional converters often suffer from high switching power...
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ISBN:
(数字)9798331543952
ISBN:
(纸本)9798331543969
The wide applications of Electric Vehicles (EVs) for integration with renewable energy sources need high-power, isolated bidirectional converters (IBC). Bi-directional converters often suffer from high switching power losses leading to efficiency reduction. Therefore many topologies are proposed to achieve soft switching and increase the converter efficiency. Among the available topologies, resonant converters (RC), such as LLC, CLLC, CLLLC, and dual active bridge (DAB) converters, are widely employed for high-power conversion because of their superior efficiency and soft-switching capabilities. In this article, a comprehensive comparative performance analysis of different RC topologies is presented. Among these, the CLLLC converter topology has emerged as a promising solution, offering higher efficiency and an extended soft-switching range compared to other RCs. Performance validation of various RCs is obtained through an experimental prototype.
This paper presents a demand-side load management technique to manage the consumption in residential buildings by maximizing the user's satisfaction at minimal cost or within a predefined budget. The load satisfac...
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The wide applications of Electric Vehicles (EVs) for integration with renewable energy sources need high-power, isolated bidirectional converters (IBC). Bi-directional converters often suffer from high switching power...
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Interactions of site-controlled quantum dots with a high-order cavity mode of an L7-type photonic crystal cavity are resolved spatially and spectrally. We observed a spatial avoided crossing in polarization-resolved o...
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The implementation of deep neural networks requires a significant amount of memory and computing power. As a result, they are often implemented in data centers or high-end computing devices such as GPUs. However, if t...
The implementation of deep neural networks requires a significant amount of memory and computing power. As a result, they are often implemented in data centers or high-end computing devices such as GPUs. However, if the internal structure of an FPGA, particularly the LUTs, is considered, the FPGA implementation of these networks could prove to be more efficient. This paper presents an iterative pruning algorithm for removing unnecessary inputs from a layer's neurons so that they can be synthesized to a small number of LUTs in an FPGA. When the number of LUTs, throughput, and power consumption are considered, our design is $7.95 \times $ smaller, $1.66 \times $ faster, and $5.66 \times $ more power efficient than the baseline, with a 0.47% accuracy drop.
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