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相关概念视频

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A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
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Electromagnetic waves can travel in the vacuum as well as in matter. For example light, which is an electromagnetic wave, can travel through air, water, or glass.
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The German physicist Heinrich Hertz (1857–1894) was the first to generate and detect certain types of electromagnetic waves in the laboratory. Starting in 1887, he performed a series of experiments that confirmed the existence of electromagnetic waves and verified that they travel at the speed of light. Hertz used an alternating-current RLC (resistor-inductor-capacitor) circuit that resonated at a known frequency and connected it to a loop of wire. High voltages induced across the gap in...
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James Clerk Maxwell formulated a single theory combining all the electric and magnetic effects scientists knew during that time, calling the phenomena his theory predicted “Electromagnetic waves”. He brought together all the work that had been done by brilliant physicists such as Oersted, Coulomb, Gauss, and Faraday and added his own insights to develop the overarching theory of electromagnetism. Maxwell’s equations, combined with the Lorentz force law, encompass all the laws...
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Electric fields generated by static charges, often referred to as electrostatic fields, are characteristically different from electric fields created by time-varying magnetic fields. While the former is a conservative field, implying that no net work is done on a test charge if it goes around in a complete loop in the field, the latter is, by definition, not a conservative field; net work is done, and it is proportional to the rate of change of magnetic flux.
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通过在无线电频率的物理计算进行分类机器学习.

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概括
此摘要是机器生成的。

我们介绍了WISE,这是一个无线边缘网络架构,可以在边缘设备上实现高效的机器学习推断. 智能显著降低了人工智能任务的能源消耗,超过了GPU.

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科学领域:

  • 计算机工程 计算机工程
  • 无线通信无线通信
  • 机器学习 机器学习

背景情况:

  • 边缘设备需要高效的机器学习来实现智能应用.
  • 传统的数字计算架构面临着边缘AI的内存和功率限制.
  • 资源受限的边缘设备限制了实时机器学习推断.

研究的目的:

  • 介绍WISE,一个用于无线边缘网络的新型计算架构.
  • 在多个边缘设备上实现高效和同时的机器学习推断.
  • 为了减少机器学习计算在边缘的能源消耗.

主要方法:

  • 开发了WISE,这是用于无线边缘网络的计算架构.
  • 通过无线无线广播实现分类模型访问.
  • 在物理中使用复杂值矩阵向量乘法在无线电频率的计算.
  • 使用软件定义的无线电平台进行实验.

主要成果:

  • 实现了95.7%的图像分类准确度和97.2%的音频分类准确度.
  • 证明的超低能耗:图像分类 6.0 fJ/MAC,音频分类 2.8 fJ/MAC.
  • 与传统数字计算 (例如GPU) 相比,能源效率提高了10倍以上.

结论:

  • 智慧为机器学习的边缘计算提供了显著的进步.
  • 拟议的架构克服了边缘AI传统数字计算的局限性.
  • 在资源受限的无线边缘设备上,WISE可实现高度准确和节能的人工智能推断.