WN:弱标准化
“弱标准化”(Weak Normalization,常缩写为WN)是物理学等学术与科学领域中的常用术语。该缩写形式便于日常书写与快速引用,提升了专业交流的效率和便捷性。
Weak Normalization具体释义
Weak Normalization的英文发音
例句
- On the one hand, it can solve the small-batch learning better and avoid the disadvantages, such as over-training, weak normalization capability, ect., of artificial neural networks prediction.
- 一方面,该方法较好地解决了小样本学习问题,避免了人工神经网等智能方法在对小批量生产工序能力进行预测时所表现出来的过学习、泛化能力弱等缺点;
- Due to narrow dynamic range and weak real-time track capability of adaptive algorithm in active control of noise, an improved adaptive algorithm with the multi error improved normalization and variational step size is investigated.
- 针对LMS算法在噪声主动控制中动态范围小和实时控制跟踪能力不强的缺点,提出了多误差改进的归一化变步长最小均方误差自适应滤波算法;
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