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In scenarios involving parallel transformers with disparate ratings, developing per-unit models requires accommodating off-nominal turns ratios. This situation arises when the selected base voltages are not proportional to the transformer’s voltage ratings. Consider a transformer where the rated voltages are related by the term a. If the chosen voltage bases satisfy a relationship involving term b, term c is defined as the ratio of these bases. This ratio is then substituted into the...
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Transformers can provide desired voltages to a circuit by modifying the number of turns in the secondary windings.
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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
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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.
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对比的前进-前进:视觉变压器的训练算法.

Hossein Aghagolzadeh1, Mehdi Ezoji1

  • 1Faculty of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, Iran.

Neural networks : the official journal of the International Neural Network Society
|July 21, 2025
PubMed
概括
此摘要是机器生成的。

相反的前进前进,一个新的大脑启发的训练算法,通过提高准确性和收速度来提高视觉转换器的性能. 这种生物学上可信的方法缩小了与反向传播的差距,在某些情况下甚至超过了它.

关键词:
反向繁殖是一种反向传播.相反的学习学习.前进-前进-前进的时间图像的分类图像的分类.视觉变压器 视觉变压器

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科学领域:

  • 人工智能的人工智能
  • 机器学习 机器学习
  • 计算神经科学是一种神经科学.

背景情况:

  • 逆向传播是训练人工神经网络的标准.
  • 前进前进 (FF) 是一种新的,生物可信的替代方案,但具有性能限制.
  • 目前的FF算法在简单的网络上进行图像分类的评估.

研究的目的:

  • 将FF算法扩展到复杂的视觉变压器 (ViT) 网络.
  • 提高FF算法的性能和生物可信性.
  • 引入了一种新型变体,即对比前进前进 (CFF).

主要方法:

  • 修改了FF算法,通过结合对比学习原理.
  • 将修改后的算法应用于视觉变压器架构.
  • 评估CFF与基线FF和反向传播相比.

主要成果:

  • CFF显著优于基线FF,精度提高了高达10%.
  • 与基线FF相比,CFF加速了融合速度的5到20倍.
  • 通过反向传播,CFF减少了绩效差距,特别是在不准确的监督下.

结论:

  • 对比前进是先进神经网络的一个有希望的,生物学上可信的训练方法.
  • 与基线FF相比,CFF表现出优越的性能和效率.
  • 在特定的机器学习任务中,CFF方法为反向传播提供了有竞争力的替代方案.