2019 IEEE 19th International Conference on Communication Technology (ICCT)最新文献_第4页

Designing Real-Time Transmission Mode for Multi-Path Communication Systems 多路径通信系统实时传输模式设计

2019 IEEE 19th International Conference on Communication Technology (ICCT) Pub Date : 2019-10-01 DOI: 10.1109/ICCT46805.2019.8947151

Zilong Zhang, Yanan Wu, Sheng-feng Chen

引用次数: 0

RefineNet-Based Speech Enhancement with Composite Metric Loss Training 基于refinenet的复合度量损失训练语音增强

2019 IEEE 19th International Conference on Communication Technology (ICCT) Pub Date : 2019-10-01 DOI: 10.1109/ICCT46805.2019.8947267

Chuan Peng, Tian Lan, Yuxin Qian, M. Li, Qiao Liu

{"title":"RefineNet-Based Speech Enhancement with Composite Metric Loss Training","authors":"Chuan Peng, Tian Lan, Yuxin Qian, M. Li, Qiao Liu","doi":"10.1109/ICCT46805.2019.8947267","DOIUrl":"https://doi.org/10.1109/ICCT46805.2019.8947267","url":null,"abstract":"Speech enhancement is a task to improve the quality and intelligibility of degraded speech. Recent work shows convolutional neural network (CNN) with encoder-decoder architecture can achieve better performance with fewer parameters than the feed-forward neural network (FNN) and recurrent neural network (RNN). It inspires us to build a CNN model based on state-of-the-art encoder-decoder architecture, RefineNet, whose effectiveness has been proved for high-resolution semantic segmentation. In this work, RefineNet is used to exploit multi-level time-frequency features for generating high-level features. Furthermore, some works concern that the inconsistency between evaluation metrics and training loss may result in failing to obtain the optimal model by training. Therefore, we take metrics as loss and composite them. Furthermore, the waveform MSE loss, which contains phase information, is also composited to compensate for using noisy phase to reconstruct enhanced speech. Experiments show our model achieves high quality and intelligibility and outperform baselines, especially at a low signal-to-noise ratio.","PeriodicalId":306112,"journal":{"name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116016955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An IPTV Video Stream Transmission Algorithm Based on Multicast and QoS 基于组播和QoS的IPTV视频流传输算法

2019 IEEE 19th International Conference on Communication Technology (ICCT) Pub Date : 2019-10-01 DOI: 10.1109/ICCT46805.2019.8947309

Jun Tao, Min Du, YunLing Zhang, Lixiang Ma

引用次数: 0

A Load Balancing Algorithm for Media Server in Distributed Trunking Communication System 分布式集群通信系统中媒体服务器的负载均衡算法

2019 IEEE 19th International Conference on Communication Technology (ICCT) Pub Date : 2019-10-01 DOI: 10.1109/ICCT46805.2019.8947150

Jiaqiang Dong, Wenfei Gong

引用次数: 0

Research on Fault Detection Technology of Information System Based on Trusted Computing 基于可信计算的信息系统故障检测技术研究

2019 IEEE 19th International Conference on Communication Technology (ICCT) Pub Date : 2019-10-01 DOI: 10.1109/ICCT46805.2019.8946998

Lijun Zhou, Haiyan Lv, Yuan Zhao, Jie Zhang

引用次数: 0

Detect Malware in Android Firmware Based on Distributed Network Environment 基于分布式网络环境的Android固件恶意软件检测

2019 IEEE 19th International Conference on Communication Technology (ICCT) Pub Date : 2019-10-01 DOI: 10.1109/ICCT46805.2019.8947099

Cam Nguyen Tan, Toàn Nguyên, Khanh Nguyen, Tuan A. Nguyen, V. Pham

引用次数: 4

ICCT 2019 Table of Contents ICCT 2019目录

2019 IEEE 19th International Conference on Communication Technology (ICCT) Pub Date : 2019-10-01 DOI: 10.1109/icct46805.2019.8947157

引用次数: 0

AdaBoost-TCP: A Machine Learning-Based Congestion Control Method for Satellite Networks 基于机器学习的卫星网络拥塞控制方法AdaBoost-TCP

2019 IEEE 19th International Conference on Communication Technology (ICCT) Pub Date : 2019-10-01 DOI: 10.1109/ICCT46805.2019.8947121

Ning Li, Z. Deng, Qiaodi Zhu, Qin Du

{"title":"AdaBoost-TCP: A Machine Learning-Based Congestion Control Method for Satellite Networks","authors":"Ning Li, Z. Deng, Qiaodi Zhu, Qin Du","doi":"10.1109/ICCT46805.2019.8947121","DOIUrl":"https://doi.org/10.1109/ICCT46805.2019.8947121","url":null,"abstract":"In a highly dynamic satellite network, frequent switching of satellite links leads to in-stability of the connection, which greatly increases the occurrence of packet loss. Existing TCP senders cannot effectively distinguish the types of network packet loss, resulting in lower network utilization. This paper proposes a machine learning-based congestion control strategy AdaBoost-TCP. AdaBoost-TCP constructs an adaptive Boost recognition model that can effectively classify the packet loss type in the satellite network. The receiver uses the model to differentiate the type of lost packets and combines the ECN flag to transmit the result to the sender. The sender adopts adaptive congestion control measures according to the type of packet loss obtained. Ada-Boost-TCP can have better classification speed and higher efficiency without increasing network load. From the ns-2 simulation results, when the packet loss rate is be-tween10-5-10-4, the AdaBoost-TCP strategy can increase throughput by up to 10% compared to Hybla, CUBIC, and Westwood. What’s more, it can achieve good fair-ness compared to NewReno.","PeriodicalId":306112,"journal":{"name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129621485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Research on Unite DAPPM with Turbo Code in Free Space Optical Communication 自由空间光通信中联合DAPPM与Turbo码的研究

2019 IEEE 19th International Conference on Communication Technology (ICCT) Pub Date : 2019-10-01 DOI: 10.1109/ICCT46805.2019.8947108

Fei Yang, Xin Ming, Yongzhe Xu, Ziqiang Huang

引用次数: 0

ISAR Speed Compensation Algorithm for High-speed Moving Target Based on Simulate Anneal 基于模拟退火的高速运动目标ISAR速度补偿算法

2019 IEEE 19th International Conference on Communication Technology (ICCT) Pub Date : 2019-10-01 DOI: 10.1109/ICCT46805.2019.8947069

B. Guo, Zhaorui Li, Yi Xiao, Lin Shi, Ning Han, Xiaoxiu Zhu

{"title":"ISAR Speed Compensation Algorithm for High-speed Moving Target Based on Simulate Anneal","authors":"B. Guo, Zhaorui Li, Yi Xiao, Lin Shi, Ning Han, Xiaoxiu Zhu","doi":"10.1109/ICCT46805.2019.8947069","DOIUrl":"https://doi.org/10.1109/ICCT46805.2019.8947069","url":null,"abstract":"When the high-speed moving target is imaging in inverse synthetic aperture radar (ISAR), the echoes are subject to inner-pulse Doppler modulation, resulting in a one-dimensional range profile broadening of the main lobe, which will affect subsequent target imaging and recognition. Aiming at the ISAR imaging of high-speed moving target, this paper proposed an inner-pulse speed compensation algorithm. Firstly, the high-speed moving target echo model is built, and the influence of high-speed motion on the chirp rate of the echo is analyzed. Secondly, the inner-pulse speed compensation of the echo is completed based on the phase compensation method, so that the echo signal satisfies the “stop-go\" model requirement. Then, let the minimum entropy of the waveform as the objective function, a target speed estimation algorithm based on simulate anneal (SA) is proposed. Finally, the simulation experiment is carried out to verify the effectiveness of the proposed algorithm. The SA algorithm used to estimate the target speed in this paper is a global optimization algorithm. It is not necessary to set the speed search range, and the algorithm has no requirement for speed prediction. Moreover, the waveform entropy is used as the objective function for optimization, and the useful information of the echo is fully utilized, which makes the algorithm has the advantages of high precision.","PeriodicalId":306112,"journal":{"name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130990053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1