2019 53rd Asilomar Conference on Signals, Systems, and Computers最新文献

Robust Source Localization Exploiting Collaborative UAV Network 基于协同无人机网络的鲁棒源定位

2019 53rd Asilomar Conference on Signals, Systems, and Computers Pub Date : 2019-11-01 DOI: 10.1109/IEEECONF44664.2019.9049002

Shuimei Zhang, Ammar Ahmed, Yimin D. Zhang

引用次数: 5

Decentralized Information Filtering Under Skew-Laplace Noise 斜拉普拉斯噪声下的分散信息滤波

2019 53rd Asilomar Conference on Signals, Systems, and Computers Pub Date : 2019-11-01 DOI: 10.1109/IEEECONF44664.2019.9049032

J. Vilà‐Valls, F. Vincent, P. Closas

引用次数: 2

Distributed Sub-gradient Algorithms with Limited Communications 有限通信的分布式子梯度算法

2019 53rd Asilomar Conference on Signals, Systems, and Computers Pub Date : 2019-11-01 DOI: 10.1109/IEEECONF44664.2019.9048683

S. Rini, Milind Rao, A. Goldsmith

{"title":"Distributed Sub-gradient Algorithms with Limited Communications","authors":"S. Rini, Milind Rao, A. Goldsmith","doi":"10.1109/IEEECONF44664.2019.9048683","DOIUrl":"https://doi.org/10.1109/IEEECONF44664.2019.9048683","url":null,"abstract":"We consider the distributed convex optimization scenario in which nodes in a network collectively find the minimum of a function utilizing only local communications and computations. Various sub-gradient algorithms have been developed for this optimization setting for the case in which the global function factorizes as the sum of local functions to be distributed to the nodes in network, including the distributed (i) online gradient descent, (ii) Nesterov gradient descent, and (iii) dual averaging algorithms. Generally speaking, these subgradient algorithms assume that, in each communication round, nodes can exchange messages of size comparable to that of the optimization variable. For many high-dimensional optimization problems, this communication requirement is beyond the capabilities of the communication network supporting the distributed optimization. For this reason, we propose a dimensionality reduction technique based on random projections to adapt these distributed optimization algorithms to networks with communication links of limited capacity. In particular, we analyze the performance of the proposed dimensionality reduction technique for the three algorithms above, i.e. (i)–(iii). Numerical simulations are presented that illustrate the performance of the proposed approach for these three algorithms.","PeriodicalId":6684,"journal":{"name":"2019 53rd Asilomar Conference on Signals, Systems, and Computers","volume":"184 1","pages":"2171-2175"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73939163","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: 4

Clutter Cancellation in Passive Radar as a Dual Basis Projection 基于双基投影的被动雷达杂波消除

2019 53rd Asilomar Conference on Signals, Systems, and Computers Pub Date : 2019-11-01 DOI: 10.1109/IEEECONF44664.2019.9048824

S. Searle, S. Howard

引用次数: 2

Neural Network DPD via Backpropagation through a Neural Network Model of the PA 通过PA的神经网络模型反向传播的神经网络DPD

2019 53rd Asilomar Conference on Signals, Systems, and Computers Pub Date : 2019-11-01 DOI: 10.1109/IEEECONF44664.2019.9048910

Chance Tarver, Liwen Jiang, Aryan Sefidi, Joseph R. Cavallaro

引用次数: 14

Waveform Design for One-Bit Radar Systems Under Uncertain Interference Statistics 不确定干扰统计下的一比特雷达系统波形设计

2019 53rd Asilomar Conference on Signals, Systems, and Computers Pub Date : 2019-11-01 DOI: 10.1109/IEEECONF44664.2019.9048693

Arindam Bose, A. Ameri, Mojtaba Soltanalian

引用次数: 1

Adaptive Beamforming Based on Interference Covariance Matrix Estimation 基于干扰协方差矩阵估计的自适应波束形成

2019 53rd Asilomar Conference on Signals, Systems, and Computers Pub Date : 2019-11-01 DOI: 10.1109/IEEECONF44664.2019.9048699

Yujie Gu, Yimin D. Zhang

引用次数: 11

Music Source Separation with Generative Adversarial Network and Waveform Averaging 基于生成对抗网络和波形平均的音乐源分离

2019 53rd Asilomar Conference on Signals, Systems, and Computers Pub Date : 2019-11-01 DOI: 10.1109/IEEECONF44664.2019.9048852

Ryosuke Tanabe, Yuto Ichikawa, Takanori Fujisawa, M. Ikehara

{"title":"Music Source Separation with Generative Adversarial Network and Waveform Averaging","authors":"Ryosuke Tanabe, Yuto Ichikawa, Takanori Fujisawa, M. Ikehara","doi":"10.1109/IEEECONF44664.2019.9048852","DOIUrl":"https://doi.org/10.1109/IEEECONF44664.2019.9048852","url":null,"abstract":"The task of music source separation is to extract a target sound from mixed sound. A popular approach for this task uses a DNN which learns the relationship of the spectrum of mixed sound and one of separated sound. However, many DNN algorithms does not consider the clearness of the output sound, this tends to produce artifact in the output spectrum. We adopt a generative adversarial network (GAN) to improve the clearness of the separated sound. In addition, we propose data augmentation by pitch-shift. The performance of DNN strongly depends on the quantity of the dataset for train. In other words, the limited kinds of the training datasets gives poor knowledge for the unknown sound sources. Learning the pitch-shifted signal can compensate the kinds of training set and makes the network robust to estimate the sound spectrum with various pitches. Furthermore, we process the pitch-shifted signals and average them to reduce artifacts. This proposal is based on the idea that network once learned can also separate pitch-shifted sound sources not only original one. Compared with the conventional method, our method achieves to obtain well-separated signal with smaller artifacts.","PeriodicalId":6684,"journal":{"name":"2019 53rd Asilomar Conference on Signals, Systems, and Computers","volume":"41 1","pages":"1796-1800"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85139954","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

Congestion Control Mechanisms in IEEE 802.11p and Sidelink C-V2X IEEE 802.11p和Sidelink C-V2X中的拥塞控制机制

2019 53rd Asilomar Conference on Signals, Systems, and Computers Pub Date : 2019-11-01 DOI: 10.1109/IEEECONF44664.2019.9048738

A. Bazzi

{"title":"Congestion Control Mechanisms in IEEE 802.11p and Sidelink C-V2X","authors":"A. Bazzi","doi":"10.1109/IEEECONF44664.2019.9048738","DOIUrl":"https://doi.org/10.1109/IEEECONF44664.2019.9048738","url":null,"abstract":"Connected vehicles are expected to play a major role in the next future to improve safety and traffic efficiency on the road and short-range technologies have been defined to enable the direct exchange of information. To this aim, two solutions are currently the subject of a debate that goes beyond the technician, i.e., IEEE 802.11p and sidelink cellular-vehicle-to-anything (C-V2X). Tested and mature for deployment the first, possibly more efficient the second. In both cases, one of the main aspects is the management of channel congestions, which can cause serious packet losses and have a critical impact on the reliability of applications. Congestions can be managed through different approaches, including the control of transmission power, packet generation frequency, and the adopted modulation and coding scheme. Congestion management has been well studied in IEEE 802.11p, with consolidated algorithms included in the standards, whereas it appears somehow as a new topic looking at C-V2X. In this work, a review of the main congestion control mechanisms and a discussion of their applicability and efficiency in the two technologies is provided. This topic is addressed without focusing on specific algorithms and with the aim to provide general guidelines as a starting point for new proposals.","PeriodicalId":6684,"journal":{"name":"2019 53rd Asilomar Conference on Signals, Systems, and Computers","volume":"9 1","pages":"1125-1130"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85197265","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: 19

Channel Estimation for Massive MIMO: A Semiblind Algorithm Exploiting QAM Structure 大规模MIMO信道估计:一种利用QAM结构的半盲算法

2019 53rd Asilomar Conference on Signals, Systems, and Computers Pub Date : 2019-11-01 DOI: 10.1109/IEEECONF44664.2019.9048774

B. Yilmaz, A. Erdogan

引用次数: 7