ID 原文 译文
17355 如何以较低的成本保证带限非平稳环境下数据传输的鲁棒性是一个非常重要的问题。 One of the most important problems is how to keep robust transmitting through band-limited non-stationary channels with low cost.
17356 该文介绍了一种低复杂度、低功耗的调制解调传输技术，即差分混沌键控(DCSK)调制。 In this overview, one low complexity, low power consumption modulation and demodulation transmittingtechnique, namely, Differential Chaos Shift Keying (DCSK) with its modified ways, is introduced in wirelessand wired transmission environment.
17357 该文将分别描述和分析该系统在标准和非标准传输环境下的特性、优势及其改进方法。 Their properties and advantages of the models under traditional and non-standard transmission environments are described and analyzed.
17358 同时将提供一些基于多元DCSK(MDCSK)的新型编码调制方案来提高系统在带限环境下的传输质量，这将有助于在低功耗、低成本的网络上，特别是在非平稳信道上提升系统的鲁棒性。 Meanwhile some new coded M-ary DifferentialChaos Shift Keying (MDCSK) schemes to enhance their quality of the system transmitting over band-limitedtransmission environments are provided, which are beneficial to improve the robust transmitting over networkswith low power consumption and low cost, particularly, over non-stationary channels.
17359 结果表明这些优化工作显著地改善了系统性能。 The results show that theoptimization work improves the system performance significantly.
17360 之后针对非平稳信道特性系统参数的优化与自适应传输机制将成为未来研究的热点。 After that, the optimization and adaptivemechanics of the system parameters for the non-stationary channel characteristics will become a future researchhotspot.
17361 针对航班延误衍生的航班延误波及问题，该文提出一种基于CBAM-CondenseNet的航班延误波及预测模型。 For the problem of flight delay propagation caused by flight delay, a flight delay wave predictionmodel based on CBAM-CondenseNet is presented.
17362 首先，通过分析航班延误在航空网络内产生的延误波及现象，确定会受前序延误航班影响的航班链； Firstly, by analyzing the delays propagation in the aviationnetwork caused by flight delays, the flight chain affected by the pre-order delays is determined;
17363 其次，对选定的航班链数据进行清洗，将航班信息与机场信息进行数据融合； Secondly, the selected flight chain data is cleaned and the flight information and airport information are fused;
17364 最后，提出改进的CBAM-CondenseNet算法对融合后的数据进行特征提取，构建Softmax分类器对首班离港航班延误波及的后续离港航班延误等级进行预测。 Finally, animproved CBAM-CondenseNet algorithm is proposed to extract the number of fused flights. According tofeature extraction, a Softmax classifier is constructed to predict the delays of the first departure flights and thesubsequent flights.