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相关概念视频

Equivalent Circuits for Practical Transformers01:28

Equivalent Circuits for Practical Transformers

398
The practical equivalent circuits of single-phase two-winding transformers exhibit significant deviations from their idealized versions due to the inherent properties of winding resistance and finite core permeability. These properties result in real and reactive power losses, affecting the transformer's performance. Understanding these deviations is crucial for designing more efficient transformers.
In a practical transformer, each winding exhibits resistance and leakage reactance. The...
398
The Ideal Transformer01:26

The Ideal Transformer

358
In single-phase two-winding transformers, two windings are coiled around a magnetic core characterized by cross-sectional area A and magnetic permeability μ. A phasor current i1 enters the left winding while i2 exits the right winding, establishing the fundamental working of the transformer through electromagnetic principles.
Ampere's Law forms the basis of understanding the magnetic field within the transformer. It states that the integral of the magnetic field intensity's...
358
Transformers01:26

Transformers

1.1K
A device that transforms voltages from one value to another using induction is called a transformer. A transformer consists of two separate coils, or windings, wrapped around the same soft iron core. However, they are electrically insulated from each other.
The iron core has a substantial relative permeability. Therefore, the magnetic field lines generated due to the current in one winding are almost entirely confined within the core, such that the same magnetic flux permeates each turn of both...
1.1K
Types Of Transformers01:16

Types Of Transformers

951
Transformers can provide desired voltages to a circuit by modifying the number of turns in the secondary windings.
If the ratio of the number of turns in the secondary winding to that of the primary winding is greater than one, then the transformer is said to be a step-up transformer. In a step-up transformer, the voltage at the secondary winding is greater than the voltage applied at the primary winding.
However, if this ratio is less than one, the transformer is said to be a step-down...
951
Energy Losses in Transformers01:21

Energy Losses in Transformers

839
In an ideal transformer, it is assumed that there are no energy losses, and, hence, all the power at the primary winding is transferred to the secondary winding. However, in reality,  the transformers always have some energy losses, and, hence, the output power obtained at the secondary winding is less than the input power at the primary winding due to energy losses.
There are four main reasons for energy losses in transformers.
The first cause can be  the high resistance of the...
839
Three-Winding Transformers01:19

Three-Winding Transformers

209
Three identical single-phase transformers can be configured to form a three-phase transformer connection, which involves high-voltage and low-voltage windings. The high-voltage windings are denoted by capital letters A-B-C, while the low-voltage windings are labeled with lowercase letters a-b-c, representing their respective phases. This notation helps distinguish between the high and low voltage sides of the transformer.
In the per-unit equivalent circuit of a grounded Y-Y three-phase...
209

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相关实验视频

Updated: Jun 10, 2025

A Method for Growing Bio-memristors from Slime Mold
07:46

A Method for Growing Bio-memristors from Slime Mold

Published on: November 2, 2017

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有效的memristor加速器用于变压器自我注意功能.

Meriem Bettayeb1,2, Yasmin Halawani3, Muhammad Umair Khan1

  • 1System-on-Chip Lab, Computer and Information Engineering, Khalifa University, Abu Dhabi, UAE.

Scientific reports
|October 15, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种使用memristor内存计算的新型硬件加速器,以克服变压器网络的计算挑战. 高效的设计显著减少了多重积累操作,同时保持了人工智能应用的高精度.

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Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
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Gradient Echo Quantum Memory in Warm Atomic Vapor
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相关实验视频

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Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
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Gradient Echo Quantum Memory in Warm Atomic Vapor
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科学领域:

  • 人工智能的人工智能
  • 计算机工程 计算机工程
  • 材料科学 材料科学 材料科学

背景情况:

  • 变压器网络在AI中变得越来越重要,但由于自我注意力机制而面临计算瓶.
  • 在自我注意的矩阵-矩阵乘法 (MatMul) 操作需要大量的内存和计算,限制了变压器的性能.
  • 卷积神经网络 (CNN) 也因其卷积操作而面临类似的约束.

研究的目的:

  • 为变压器网络开发一个高效的硬件加速器.
  • 为了解决与自我注意机制的MatMul操作相关的内存和计算复杂性.
  • 为了实现边缘设备上的变压器架构的实时性能.

主要方法:

  • 利用基于memristor的内存计算来实现硬件加速.
  • 在memristor交叉杆架构中利用近似模拟计算.
  • 在自我注意过程中针对MatMul操作的记忆瓶.

主要成果:

  • 在变压器网络的多重积累 (MAC) 操作中实现了大约10倍的减少.
  • 在MNIST数据集上保持了高准确度 (95.47%).
  • 证明了模拟结果与特定区域利用率,延迟,能源消耗和泄漏功率指标.

结论:

  • 拟议的基于memristor的加速器为硬件友好的变压器架构提供了重大进步.
  • 这种方法有效地减轻了自我注意机制的计算复杂性.
  • 该方法为边缘设备的高效实时变压器部署铺平了道路.