| 1. | The classical approach is to start with a blank piece of paper , and write down , in any order , all important ideas that occur to you concerning the paper
最经典的方法就是找一页空白的纸，以任何顺序，写下与这篇文章有关的所有重要观点。 |
| 2. | Finally , in the application of the resistance matrix , the calculation of the acoustic field has been avoided , giving a degree of accuracy comparable to the classical approaches
利用阻力矩阵法，不仅避免了声场的计算，而且能达到经典法所能达到的精度。 |
| 3. | Though the conventional single - population - based genetic algorithms ( csgas ) can find solutions with better quality than classical approaches for scheduling problems , the efficacy and efficiency of csga decrease with the number of tasks
尽管已有用于任务分配与调度的遗传算法的求解质量优于传统方法，但传统单种群遗传算法的效率随任务数增多而下降。 |
| 4. | In order to overcome the restriction of classical approaches of stability for linear time - invariant discrete large - scale systems , we study the stability for large - scale systems with unidirectional strong coupling among subsystems in chapter 2
为了克服传统大系统稳定性分析方法的局限性，在第二章研究子系统间具有单向强耦合的线性定常离散大系统的稳定性问题。 |
| 5. | In this paper , we first comment on the classical approach , then present an effective modern approach based on process capability indices for measuring manufacturing process quality , specifically for high technology product requiring very low fraction of nonconformities ( often measured in ppm , parts per million )
有鉴于此，本研究提出一个评估高科技产品制程质量水?的有效方法，也就是利用制程能力指针来评估制程能力与产出绩效。 |
| 6. | After the state of arts of image segmentation technique is introduced , the key techniques of classical approaches ( threshold and edge detection method ) are presented . then the performance of these approaches are analyzed and validated through a group of experiments
论文首先阐述了图象分割及目标跟踪技术的发展和现状,并对图象分割方法中的关键技术(边缘检测法和阈值分割法)进行了详细介绍,然后通过实验对几种经典的阈值分割算法进行了验证和分析。 |
| 7. | A serial generalized morphological filter with multi - structural element is used suppression white gaussian noise or pulse noise embedded in the speech signal . the paper compares morphological speech enhancement algorithm with classical approach on the feature of speech in the frequency domain and time domain
本文针对形态学在数字语音信号增强中的应用算法研究，采用多结构元素的广义形态滤波器，主要用于对被高斯白噪声或正负脉冲噪声污染的语音信号的滤波增强，深入研究形态学滤波的语音增强算法在语音时域、频域对语音特征参数的影响。 |
