SCI论文选词炼句（下）
目录：
SCI论文选词炼句（上）-CSDN博客
SCI论文选词炼句（中）-CSDN博客
Principle
C
原句：
As analyzed in the previous section, when noise intensity increases, the multi-signal regression box becomes wider and fails to fit the target signal, making parameter estimation using this box inaccurate. The previous section also highlighted the decoupled characteristics between multi-signal detection, recognition, and parameter estimation tasks, which can be leveraged to improve parameter estimation accuracy. The red arrow in Fig. \ref{fig_3D_arrow} points to the step feature between the target signal and background noise, a specific manifestation of the decoupled characteristic. Under low SNR, it no longer contributes to the classification accuracy of the target signal but still plays a role in improving regression box precision, thereby enhancing MSPE precision.
精简润色：
As discussed earlier, increased noise broadens the multi-signal regression box, reducing its fit to the target and leading to inaccurate parameter estimation. The decoupling between detection, recognition, and estimation tasks can be exploited to improve estimation accuracy. In Fig. \ref{fig_3D_arrow}, the red arrow highlights a step feature between the target and background noise—an example of this decoupling. Under low SNR, it no longer aids classification but still enhances box precision, thereby improving MSPE accuracy.
人工优化：
As discussed earlier, increased noise broadens the multi-signal regression box, reducing its fit to the target and leading to imprecise parameter estimation. The decoupling between recognition and estimation tasks can be exploited to improve estimation precision. In Fig. \ref{fig_3D_arrow}, the red arrow highlights a step feature between the target and background noise—an example of this decoupling. Under low SNR, it no longer aids classification but still enhances box precision, thereby improving MSPE precision.
原句：
We abstracted the RBO Algorithm from the natural phenomenon where a rubber band overcomes complex surface resistance to contract to the object’s outline. This algorithm is applied to MSPE task with decoupled characteristics, improving MSPE precision by utilizing the step feature between the target signal and background noise. As shown in Fig. \ref{Fig_Rubber_band_biomimetic}, the white object is our 3D-printed multi-signal time-frequency diagram resin model, which intuitively demonstrates the RBO Algorithm. In Fig. \ref{Fig_Rubber_band_biomimetic}(a), the box fully constructed from wooden sticks represents the parameter estimation box obtained directly from a DL object detection framework, with the rigidity of the sticks indicating that the parameter estimation box cannot adapt to the environment and is entirely determined by the DL architecture. In Fig. \ref{Fig_Rubber_band_biomimetic}(b), the box's left and right sides are made of rubber bands. We use the elasticity of the rubber bands to give the parameter estimation box adaptability to the environment, allowing it to align with the target signal even under low SNR, achieving high-precision parameter estimation.
精简风格Chat GPT润色：
The RBO algorithm is inspired by the natural phenomenon of a rubber band contracting to an object’s contour by overcoming complex surface resistance. It is applied to the MSPE task by leveraging the decoupled characteristics, enhancing estimation precision through the step feature between the target signal and background noise. As shown in Fig. \ref{Fig_Rubber_band_biomimetic}, the white object is a 3D-printed resin model of the multi-signal time-frequency diagram, intuitively demonstrating the RBO concept. In Fig. \ref{Fig_Rubber_band_biomimetic}(a), the box constructed entirely from wooden sticks represents the parameter estimation box directly output by a DL-based object detector, with the stick rigidity symbolizing its lack of adaptability. In contrast, Fig. \ref{Fig_Rubber_band_biomimetic}(b) replaces the box’s sides with rubber bands, whose elasticity allows the estimation box to adapt to signal contours under low SNR, enabling high-precision estimation.
人工优化：
The RBO algorithm is inspired by the natural phenomenon of a rubber band contracting to an object’s contour by overcoming complex surface resistance. It is applied to the MSPE task by leveraging the decoupled characteristics, enhancing estimation precision through the step feature between the target signal and background noise. As shown in Fig. \ref{Fig_Rubber_band_biomimetic}, the white object is a 3D-printed resin model of the multi-signal time-frequency diagram, intuitively demonstrating the RBO concept. In Fig. \ref{Fig_Rubber_band_biomimetic}(a), the box constructed entirely from wooden sticks represents the parameter estimation box directly output by a DL-based object detector, with the stick rigidity symbolizing its lack of adaptability. In contrast, Fig. \ref{Fig_Rubber_band_biomimetic}(b) replaces the box’s sides with rubber bands, whose elasticity allows the estimation box to adapt to signal contours under low SNR, enabling high-precision estimation.
原句：
Below is an analysis of the rubber band's action on a 3D-printed multi-signal time-frequency diagram resin model. Through this analysis, we abstract key properties of the rubber band and program them into the object detection DL model's prediction box. This enables the model to maintain good regression characteristics under low SNR, utilizing MSPE. The rubber band's stretching process is filled with internal stress:
人工优化：
We analyze the behavior of a rubber band acting on a 3D-printed resin model of a multi-signal time-frequency diagram to abstract its key properties and embed them into the prediction box of the DL-based object detection model. This enhances regression performance under low SNR for MSPE. The stretching process of the rubber band inherently involves internal stress:
精简风格Chat GPT润色：
We analyze the behavior of a rubber band acting on a 3D-printed resin model of a multi-signal time-frequency diagram to abstract its key properties and embed them into the prediction box of the object detection DL model. This enhances regression performance under low SNR for MSPE. The stretching process of the rubber band inherently involves internal stress: