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2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)最新文献

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A channel matching based hybrid analog-digital strategy for massive multi-user MIMO downlink systems 基于信道匹配的大规模多用户MIMO下行系统混合模数策略
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569693
Jianshu Zhang, M. Haardt, I. Soloveychik, A. Wiesel
{"title":"A channel matching based hybrid analog-digital strategy for massive multi-user MIMO downlink systems","authors":"Jianshu Zhang, M. Haardt, I. Soloveychik, A. Wiesel","doi":"10.1109/SAM.2016.7569693","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569693","url":null,"abstract":"In this paper we study the downlink of a hybrid analog-digital massive multi-user MIMO (MU-MIMO) system. An efficient hybrid strategy is proposed, where the analog beamforming matrices are determined using a channel matching criterion while the digital beamforming consists of pre-filters and post-filters. The digital post-filters are computed using traditional linear MU-MIMO strategies together with water-filling based power allocation using the effective channels. Simulation results show that the proposed hybrid analog-digital solutions achieve a good performance compared to their corresponding unconstrained digital solutions.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126613354","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: 24
Reduced-rank filtering on L1-norm subspaces l1范数子空间上的降秩滤波
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569743
Panos P. Markopoulos
{"title":"Reduced-rank filtering on L1-norm subspaces","authors":"Panos P. Markopoulos","doi":"10.1109/SAM.2016.7569743","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569743","url":null,"abstract":"Recent studies in signal processing have unveiled the remarkable outlier-resistance properties of L1-norm subspaces, calculated by means of L1-norm principal component analysis (L1-PCA). In this work, we present for the first time reduced-rank interference-suppressive filtering on L1-norm subspaces of the received signal vectors. Our simulation studies illustrate that the proposed filtering framework allows for successful suppression of coherent interference while, at the same time, it offers sturdy protection against outliers that appear among the training samples.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128085038","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: 15
Modelling time series via automatic learning of basis functions 通过基函数的自动学习建模时间序列
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569727
Felipe A. Tobar, Richard E. Turner
{"title":"Modelling time series via automatic learning of basis functions","authors":"Felipe A. Tobar, Richard E. Turner","doi":"10.1109/SAM.2016.7569727","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569727","url":null,"abstract":"We present a model for time series consisting of an infinite mixture of basis functions, whereby the bases and the mixing process are modelled as posterior means of latent Gaussian processes (GPs). Conditional to observed data, the bases and the mixing process are learnt using a parametric approximation based on pseudo-observations, where the complexity and accuracy of the method are controlled by the number of pseudo-observations (Nx and Nh). The resulting model is linear the pseudo-observations, and its likelihood function has a complexity O(NNhNx), Nx <; N, Nh ≪ N, which is lower than that of the standard GP O(N3) - where N is the number of observations. We validate the proposed approach using synthetic data, where we recovered latent GPs with five different kernels from noisy observations; and using a real-world heart-rate signal to assess the proposed model's computational complexity and performance.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128129288","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: 2
Reception filter impact on widely linear fresh receiver performance for SAIC/MAIC with frequency offsets 带频偏的上汽/MAIC接收滤波器对宽线性新鲜接收机性能的影响
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569723
P. Chevalier, J. Delmas, Rémi Chauvat
{"title":"Reception filter impact on widely linear fresh receiver performance for SAIC/MAIC with frequency offsets","authors":"P. Chevalier, J. Delmas, Rémi Chauvat","doi":"10.1109/SAM.2016.7569723","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569723","url":null,"abstract":"Widely linear (WL) receivers are able to fulfill single antenna interference cancellation (SAIC) of one rectilinear (R) (ASK, BPSK) or quasi-rectilinear (QR) (MSK, GMSK, OQAM) co-channel interference (CCI). In the presence of residual frequency offsets (FO), standard SAIC/MAIC receivers lose their efficiency and have to be extended using WL frequency shifted (FRESH) filtering, which has been done recently. However, in practice the observations are low-pass filtered before sampling and processing, which may degrade the performance. In this context, the purpose of the paper is twofold. The first one is to extend the previous pseudo MLSE-based WL FRESH receiver, for sources with differential FO, to observations which are low-pass filtered. The second one is to analyze, both analytically and by simulations, the impact of the low-pass filtering on the performance of the extended pseudo MLSE-based WL FRESH receiver.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125873180","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
On spatial aspect decorrelation in SAR and ISAR SAR与ISAR的空间向去相关研究
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569721
Stefan Brisken, H. Tran
{"title":"On spatial aspect decorrelation in SAR and ISAR","authors":"Stefan Brisken, H. Tran","doi":"10.1109/SAM.2016.7569721","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569721","url":null,"abstract":"This paper is dedicated to the phenomenon that radar observations from large angular variations cannot be integrated coherently if standard SAR/ISAR signal processing is applied. The reasons for this spatial aspect decorrelation are elucidated and a methodology for its characterization is introduced. Finally, the new methodology is used to compare the spatial aspect decorrelation of the standard point scatterer signal model to a signal model where the elementary scatterers are assumed to be tilted wires.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126590270","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
Improving learning efficiency in multi-objective simulated annealing programming for sound environment classification 提高声环境分类多目标模拟退火规划的学习效率
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569699
A. Cocaña-Fernández, L. Sánchez, J. Ranilla, R. Gil-Pita, Héctor A. Sánchez-Hevia
{"title":"Improving learning efficiency in multi-objective simulated annealing programming for sound environment classification","authors":"A. Cocaña-Fernández, L. Sánchez, J. Ranilla, R. Gil-Pita, Héctor A. Sánchez-Hevia","doi":"10.1109/SAM.2016.7569699","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569699","url":null,"abstract":"In this work, a classifier that jointly optimises the expected total classification cost and the energy consumption is presented. A numerical study is provided, where different alternatives are implemented on a hearing aid. Our proposal is capable of automatically classifying the acoustic environment that surrounds the user and choosing the parameters of the amplification that are best adapted to the user's comfort, while attaining relevant improvements in both classification and learning-related energy consumptions with small to negligible loss in classification accuracy.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122595330","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
Adaptive population importance samplers: A general perspective 适应性种群重要性样本:概观
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569668
Luca Martino, V. Elvira, D. Luengo, F. Louzada
{"title":"Adaptive population importance samplers: A general perspective","authors":"Luca Martino, V. Elvira, D. Luengo, F. Louzada","doi":"10.1109/SAM.2016.7569668","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569668","url":null,"abstract":"Importance sampling (IS) is a well-known Monte Carlo method, widely used to approximate a distribution of interest using a random measure composed of a set of weighted samples generated from another proposal density. Since the performance of the algorithm depends on the mismatch between the target and the proposal densities, a set of proposals is often iteratively adapted in order to reduce the variance of the resulting estimator. In this paper, we review several well-known adaptive population importance samplers, providing a unified common framework and classifying them according to the nature of their estimation and adaptive procedures. Furthermore, we interpret the underlying motivation for the different adaptation schemes, opening the door for novel and more efficient algorithms. Finally, we compare the performance of different algorithms available in the literature through a toy example.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123078339","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: 6
Ultra-wideband radar and vision based human motion classification for assisted living 辅助生活中基于超宽带雷达和视觉的人体运动分类
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569747
Zhichong Zhou, J. Zhang, Yimin D. Zhang
{"title":"Ultra-wideband radar and vision based human motion classification for assisted living","authors":"Zhichong Zhou, J. Zhang, Yimin D. Zhang","doi":"10.1109/SAM.2016.7569747","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569747","url":null,"abstract":"Fall detection for elderly is one of the most important areas in elderly healthcare. Both video and radar based detections are being developed for this purpose. This paper presents a new approach to classify different human motions through machine learning. In particular, our objective is to achieve high-accuracy fall detection through the exploitation of both video and radar data. Motion history image is applied to extract temporal features from video clips, and hidden Markov models are trained with the features extracted from both video and radar data to discern the types of motion. Experiment results indicate that the proposed approach provides improved performance in distinguishing falls from other motions such as sitting.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124801351","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: 5
Incremental multiple error filtered-X LMS for node-specific active noise control over wireless acoustic sensor networks 基于增量多误差滤波的LMS无线声传感器网络有源噪声控制
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569667
J. Plata-Chaves, A. Bertrand, M. Moonen
{"title":"Incremental multiple error filtered-X LMS for node-specific active noise control over wireless acoustic sensor networks","authors":"J. Plata-Chaves, A. Bertrand, M. Moonen","doi":"10.1109/SAM.2016.7569667","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569667","url":null,"abstract":"We propose an adaptive distributed algorithm to solve a node-specific Active Noise Control (ANC) problem. In this novel ANC problem, the nodes estimate different but overlapping ANC filters in order to generate secondary signals that cancel a primary noise source as it impinges on their microphones. Different sets of nodes follow a cyclic mode of cooperation in order to implement several coupled Multiple Error Filtered-X Least Mean Squares algorithms, each responsible for the estimation of part of the different node-specific ANC filters. The proposed algorithm outperforms the non-cooperative strategies and achieves the same steady-state noise reduction as a centralized solution that processes all the signals in the network. Finally, computer simulations are provided to illustrate the effectiveness of the proposed algorithm.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124806069","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: 25
Multi-task wireless acoustic sensor network for node-specific speech enhancement and DOA estimation 多任务无线声学传感器网络中特定节点的语音增强和DOA估计
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569718
Amin Hassani, J. Plata-Chaves, A. Bertrand, M. Moonen
{"title":"Multi-task wireless acoustic sensor network for node-specific speech enhancement and DOA estimation","authors":"Amin Hassani, J. Plata-Chaves, A. Bertrand, M. Moonen","doi":"10.1109/SAM.2016.7569718","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569718","url":null,"abstract":"We consider the design of a distributed algorithm that is suitable for a wireless acoustic sensor network formed by nodes solving multiple tasks (MDMT). In the network, some of the nodes aim at estimating the node-specific direction-of-arrival of some desired sources. Additionally, there are other nodes that aim at implementing either a multi-channel Wiener filter or a minimum variance distortionless response beamformer in order to estimate node-specific desired signals as they impinge on their microphones. By using compressive filter-and-sum operations that incorporate a low-rank approximation of the sensor signal correlation matrix, the proposed MDMT algorithm let the nodes cooperate to achieve the network-wide centralized solution of their node-specific estimation problems without any knowledge about the tasks of other nodes. Finally, the effectiveness of the algorithm is shown through computer simulations.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131736122","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
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