Equivalent Circuits for Practical Transformers
The Ideal Transformer
Three-Winding Transformers
Types Of Transformers
Energy Losses in Transformers
Transformers
您也可能阅读
通过共同作者、期刊和引用图与本文相关的文章。
Updated: May 14, 2025

Lensless Fluorescent Microscopy on a Chip
Published on: August 17, 2011
1SCS Laboratory, Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5, Kashiwa-no-ha, Kashiwa City 277-8563, Chiba, Japan.
本研究介绍了双升级启发变压器 (DAT),这是用于图像压缩传感 (CS) 的灵活深度学习模型. 在各种压缩比下,DAT实现了高质量的重建,并大大减少了训练时间和成本.
科学领域:
背景情况:
研究的目的:
主要方法:
主要成果:
结论: