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相关概念视频

Masking and Demasking Agents01:19

Masking and Demasking Agents

3.4K
EDTA titrations may necessitate masking and demasking agents to temporarily protect a particular metal ion in a mixture from the EDTA reaction. These agents facilitate the sequential analysis of the metal ions by forming stable complexes with some—but not all—metal ions during certain steps.
There are many masking agents, such as cyanide, fluoride, triethanolamine, thiourea, and 2,3-bis(sulfanyl)propan-1-ol (formerly 2,3-dimercapto-1-propanol), with the masking agent chosen based on...
3.4K
Biasing of FET01:22

Biasing of FET

648
Biasing a Junction Field Effect Transistor (JFET) is crucial for setting operational parameters and ensuring efficient functioning in electronic circuits. JFETs are characterized by using a single carrier type in N-channel or P-channel configurations, where the channel is surrounded by PN junctions. These junctions are central to the device's ability to control current flow.
In an N-channel JFET, the structure consists of N-type material forming the channel on a P-type substrate, with the...
648
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

371
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
371
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

705
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
705
Statically Indeterminate Problem Solving01:16

Statically Indeterminate Problem Solving

663
Statically indeterminate problems are those where statics alone can not determine the internal forces or reactions. Consider a structure comprising two cylindrical rods made of steel and brass. These rods are joined at point B and restrained by rigid supports at points A and C. Now, the reactions at points A and C and the deflection at point B are to be determined. This rod structure is classified as statically indeterminate as the structure has more supports than are necessary for maintaining...
663
Synthetic Disvision of Polynomials01:28

Synthetic Disvision of Polynomials

117
Synthetic division is an efficient algorithmic approach for dividing a polynomial by a linear binomial of the form x - c, where c is a real number. This method is helpful due to its streamlined process, which avoids the more cumbersome steps involved in the traditional long division of polynomials. It simplifies computation and serves as a practical tool for evaluating polynomials and identifying their factors.To perform synthetic division, one begins by listing the coefficients of the...
117

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相关实验视频

Updated: Jan 7, 2026

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

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运行时强大的边缘推理系统,在动态重配置FPGA上进行基于掩盖的部分更新.

Myeongjin Kang1, Daejin Park2

  • 1School of Electronic and Electrical Engineering, Kyungpook National University, Daegu 41566, Republic of Korea.

Sensors (Basel, Switzerland)
|December 31, 2025
PubMed
概括

这项研究引入了一个新的边缘推理框架,用于在动态环境中实时适应. 它使用服务器端的FPGA进行掩盖更新,降低了强大的边缘AI的延迟和通信成本.

关键词:
在FPGA加速器上.动态部分重新配置动态部分重新配置.边缘云系统的边缘云系统.学习加速器学习加速器

相关实验视频

Last Updated: Jan 7, 2026

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

5.0K

科学领域:

  • 边缘计算 边缘计算
  • 人工智能的人工智能
  • 硬件加速器 硬件加速器

背景情况:

  • 边缘推理系统需要在环境变化 (如传感器噪声和新对象类) 中实时性能.
  • 边缘设备上的静态,离线训练模型由于输入分布漂移而降低准确性.

研究的目的:

  • 提出一个运行时强大的边缘推理框架,允许在没有执行中断的情况下进行持续的调整.
  • 为了利用服务器端的FPGA加速,在边缘设备上进行高效,动态的模型更新.

主要方法:

  • 在边缘设备上将内存分成主动和自适应区域.
  • 服务器端的FPGA执行层级重要性分析和部分再培训.
  • 动态部分重新配置 (DPR) 用于自适应的面具生成和最小化重新配置延迟.

主要成果:

  • 与GPU全面重新训练相比,适应延迟降低了1.3倍.
  • 通信成本降至28%的完整模型传输.
  • 证明了实时适应性,低延迟和通信效率.

结论:

  • 拟议的框架有效地将基于掩盖的选择性更新与FPGA DPR加速相结合.
  • 在云端协作环境中实现强大的实时学习和适应.
  • 为动态边缘推理挑战提供了可行的解决方案.