The basic principle was analyzed by using a Gaussian input short pulse and its characteristics were discussed by numerical simulation.
使用高斯输入短脉冲及其特点进行了讨论，通过数值模拟的基本原理进行了分析。
In prediction and modeling, most the responses were found to be best trained using Gaussian input membership functions with a linear output function.
在预测和建模中，通过大量研究发现，最好使用高斯输入函数和线性输出函数。
Traditional short-term autocorrelation-based adaptive line spectrum enhancer (SABALSE) becomes low in suppressing Gaussian noise when input signal-to-noise ratio becomes low.
通常的基于短时自相关的自适应线谱增强器（SABALSE）主要缺点是：输入信噪比低时，抑制高斯噪声性能差。
Classical saliency-based visual attention models are adapted for embedding real-time systems with less time and space costs based on approximate Gaussian pyramids of the input image.
利用输入图像的近似高斯金字塔，将经典的基于显著性的视觉注意模型改造为时空开销更小的版本，从而使其更加适合在嵌入式实时系统中实现。
Classical saliency-based visual attention models are adapted for embedding real-time systems with less time and space costs based on approximate Gaussian pyramids of the input image.
利用输入图像的近似高斯金字塔，将经典的基于显著性的视觉注意模型改造为时空开销更小的版本，从而使其更加适合在嵌入式实时系统中实现。
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