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2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)最新文献

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A Modified Frequency Weighted MUSIC Algorithm for Multiple Sound Sources Localization 一种改进的频率加权MUSIC多声源定位算法
2018 IEEE 23rd International Conference on Digital Signal Processing (DSP) Pub Date : 2018-11-01 DOI: 10.1109/ICDSP.2018.8631636
Shan Gao, Yankun Huang, Zhang Tao, Xihong Wu, T. Qu
{"title":"A Modified Frequency Weighted MUSIC Algorithm for Multiple Sound Sources Localization","authors":"Shan Gao, Yankun Huang, Zhang Tao, Xihong Wu, T. Qu","doi":"10.1109/ICDSP.2018.8631636","DOIUrl":"https://doi.org/10.1109/ICDSP.2018.8631636","url":null,"abstract":"The traditional weighted MUSIC algorithm is usually implemented based on a sparsity assumption named W-Disjoint Orthogonality (WDO) when the number of sound sources is unknown, which may not be suitable in many scenarios. In this paper, a modified weighted MUSIC algorithm is proposed to improve the localization performance in multiple sound sources. Instead of using the maximum eigenvalue as the weight of each frequency band, we use the signal-to-noise ratio (SNR) as the weight coefficient of each frequency band, which can reduce the disturbance cases by the multiple sources bands. The simulation experiments are conducted to evaluate the performance of our proposed method and compare with the traditional weighted MUSIC algorithm. The results show that the proposed algorithms have a better localization accuracy in multiple-source environment.","PeriodicalId":218806,"journal":{"name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","volume":"147 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127260268","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
Long-range speech acquirement and enhancement with dual-point laser Doppler vibrometers 双点激光多普勒振动仪的远程语音采集与增强
2018 IEEE 23rd International Conference on Digital Signal Processing (DSP) Pub Date : 2018-11-01 DOI: 10.1109/ICDSP.2018.8631671
Renhua Peng, Binbin Xu, Guoteng Li, C. Zheng, Xiaodong Li
{"title":"Long-range speech acquirement and enhancement with dual-point laser Doppler vibrometers","authors":"Renhua Peng, Binbin Xu, Guoteng Li, C. Zheng, Xiaodong Li","doi":"10.1109/ICDSP.2018.8631671","DOIUrl":"https://doi.org/10.1109/ICDSP.2018.8631671","url":null,"abstract":"This paper presents a long-range speech acquirement and speech enhancement system by utilizing two laser Doppler vibrometers (LDV) to measure two separate points on only one vibration object or two different vibration objects. This proposed LDV system can provide dual-channel synchronous signals, and thus the coherent-to-diffused ratio-based and the multi-channel linear prediction-based algorithms can be introduced to reduce the reverberation and the noise of the acquired speech signals. The two algorithms are combined together to further improve the speech enhancement performance. Experimental results show that the proposed algorithm can significantly improve the PESQ scores.","PeriodicalId":218806,"journal":{"name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126460415","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
Learning Approach with Random Forests on Vehicle Detection 随机森林在车辆检测中的学习方法
2018 IEEE 23rd International Conference on Digital Signal Processing (DSP) Pub Date : 2018-11-01 DOI: 10.1109/ICDSP.2018.8631871
Li-Wen Wang, Xuefei Yang, W. Siu
{"title":"Learning Approach with Random Forests on Vehicle Detection","authors":"Li-Wen Wang, Xuefei Yang, W. Siu","doi":"10.1109/ICDSP.2018.8631871","DOIUrl":"https://doi.org/10.1109/ICDSP.2018.8631871","url":null,"abstract":"A Close-up Monitoring System (CMS) has been designed in our research laboratory, which aims at avoiding any potential collision risk by detecting the frontal train’s distance from the captured video. Histogram of orientated gradient (HOG) has been used as a feature descriptor, because it gives robust performance in various illumination conditions. Random forest algorithm is a conventional machine learning tool, but it is new in the driving assistant application. Besides, the predicting process of our classifier is very fast because it only depends on a limited number of simple tests in each randomly-trained decision tree. Based on the HOG features and random forest algorithm, a close-range train detector has been designed. This proposed detector works as one detection module in CMS, and the correct detection rate of the close-range train was nearly 100%, which means there was no miss-detection in our control experiment. Compared with the traditional non-learning method, our learning-based approach achieves much stronger recognition ability with less false alarms.","PeriodicalId":218806,"journal":{"name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128756371","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
Dummy Signal Precoding for PAPR Reduction in MIMO Communication System MIMO通信系统中减小PAPR的虚信号预编码
2018 IEEE 23rd International Conference on Digital Signal Processing (DSP) Pub Date : 2018-11-01 DOI: 10.1109/ICDSP.2018.8631848
Kai Kang, Zhou Fang, Haifeng Wang, H. Qian, Yang Yang
{"title":"Dummy Signal Precoding for PAPR Reduction in MIMO Communication System","authors":"Kai Kang, Zhou Fang, Haifeng Wang, H. Qian, Yang Yang","doi":"10.1109/ICDSP.2018.8631848","DOIUrl":"https://doi.org/10.1109/ICDSP.2018.8631848","url":null,"abstract":"Modern communication signals such as orthogonal frequency division multiplexing (OFDM) signals suffers from large peak-to-average power ratio (PAPR), which may sacrifice power efficiency and/or distort the signal in the presence of radio front end nonlinearity. In this paper, we propose a dummy signal precoding method to deal with the inherent PAPR problem in a multiple-input multiple-output OFDM (MIMO-OFDM) system. The idea is to generate a set of random dummy signals and combine them with existing input data. Precoding is applied to eliminate the multiuser interference. The signal with low PAPR is chosen for transmission. Simulation shows that the proposed method can effectively reduce the PAPR of the transmit signal. In addition, no side information needs to be transmitted with the proposed method. Thus the proposed method complies with existing MIMO-OFDM architecture.","PeriodicalId":218806,"journal":{"name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128611534","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
A Unified Framework for Caching in Arbitrary Networks 任意网络中缓存的统一框架
2018 IEEE 23rd International Conference on Digital Signal Processing (DSP) Pub Date : 2018-11-01 DOI: 10.1109/ICDSP.2018.8631684
Yawei Lu, Wei Chen, H. Poor
{"title":"A Unified Framework for Caching in Arbitrary Networks","authors":"Yawei Lu, Wei Chen, H. Poor","doi":"10.1109/ICDSP.2018.8631684","DOIUrl":"https://doi.org/10.1109/ICDSP.2018.8631684","url":null,"abstract":"Proactive caching holds the promise of improving network throughput and lowering transmission costs in content-centric networks. However, how to encode data in cache-aided networks is still an open problem. In this paper, a two-phase caching system is investigated, in which users are equipped with buffers and user requests are characterized by a probability measure. Based on content division, a unified framework for caching in arbitrary networks is presented. From the perspective of linear space, optimization problems are formulated to obtain the optimal linear coded joint placement and delivery (LCJPD) policy. A low-complexity algorithm is also proposed to give a sub-optimal LCJPD policy. Simulation results demonstrate that caching in networks can significantly reduce the transmission cost.","PeriodicalId":218806,"journal":{"name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131716697","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
Design of FIR Filter Based on Algebraic Integer Quantization 基于代数整数量化的FIR滤波器设计
2018 IEEE 23rd International Conference on Digital Signal Processing (DSP) Pub Date : 2018-11-01 DOI: 10.1109/ICDSP.2018.8631667
Zeguo Yang, Ma Shang, Shuai Hu, Kun Zheng, Xuyuan Cao, Jienan Chen
{"title":"Design of FIR Filter Based on Algebraic Integer Quantization","authors":"Zeguo Yang, Ma Shang, Shuai Hu, Kun Zheng, Xuyuan Cao, Jienan Chen","doi":"10.1109/ICDSP.2018.8631667","DOIUrl":"https://doi.org/10.1109/ICDSP.2018.8631667","url":null,"abstract":"Finite impulse response (FIR) digital filter is one of the key computational units in modern digital signal processing (DSP) systems. This paper presents a design method based on algebraic integer quantization for FIR digital filter with constant coefficients. To quantify the filter coefficients by appropriate algebraic integer, the multipliers can be replaced by the few adders, thereby reducing the implementation complexity. Compared with the traditional architectures, this method is faster and saves about 10%-20% in area. At the same time, this method has a better interconnection structure, which makes the area increment smaller when the timing constraints are strengthened.","PeriodicalId":218806,"journal":{"name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131835701","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
Automatic Verbal Analysis of Interviews with Schizophrenic Patients 精神分裂症患者访谈的自动言语分析
2018 IEEE 23rd International Conference on Digital Signal Processing (DSP) Pub Date : 2018-11-01 DOI: 10.1109/ICDSP.2018.8631830
Shihao Xu, Zixu Yang, Debsubhra Chakraborty, Yasir Tahir, Tomasz Maszczyk, Y. H. V. Chua, J. Dauwels, D. Thalmann, N. Magnenat-Thalmann, Bhing-Leet Tan, J. Lee
{"title":"Automatic Verbal Analysis of Interviews with Schizophrenic Patients","authors":"Shihao Xu, Zixu Yang, Debsubhra Chakraborty, Yasir Tahir, Tomasz Maszczyk, Y. H. V. Chua, J. Dauwels, D. Thalmann, N. Magnenat-Thalmann, Bhing-Leet Tan, J. Lee","doi":"10.1109/ICDSP.2018.8631830","DOIUrl":"https://doi.org/10.1109/ICDSP.2018.8631830","url":null,"abstract":"Schizophrenia is a long-term mental disease associated with language impairments that affect about one percent of the population. Traditional assessment of schizophrenic patients is conducted by trained professionals, which requires tremendous resources of time and effort. This study is part of a larger research objective committed to creating automated platforms to aid clinical diagnosis and understanding of schizophrenia. We have analyzed non-verbal cues and movement signals in our previous work. In this study, we explore the feasibility of using automatic transcriptions of interviews to classify patients and predict the observability of negative symptoms in schizophrenic patients. Interview recordings of 50 schizophrenia patients and 25 age-matched healthy controls were automatically transcribed by a speech recognition toolkit. After which, Natural Language Processing techniques were applied to automatically extract the lexical features and document vectors of transcriptions. Using these features, we applied ensemble machine learning algorithm (by leave-one-out cross-validation) to predict the Negative Symptom Assessment subject ratings of schizophrenic patients, and to classify patients from controls, achieving a maximum accuracy of 78.7%. These results indicate that schizophrenic patients exhibit significant differences in lexical usage compared with healthy controls, and the possibility of using these lexical features in the understanding and diagnosis of schizophrenia.","PeriodicalId":218806,"journal":{"name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","volume":" 111","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132188031","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: 8
An Efficient Data-Driven False Data Injection Attack in Smart Grids 智能电网中一种有效的数据驱动假数据注入攻击
2018 IEEE 23rd International Conference on Digital Signal Processing (DSP) Pub Date : 2018-11-01 DOI: 10.1109/ICDSP.2018.8631857
Fuxi Wen, W. Liu
{"title":"An Efficient Data-Driven False Data Injection Attack in Smart Grids","authors":"Fuxi Wen, W. Liu","doi":"10.1109/ICDSP.2018.8631857","DOIUrl":"https://doi.org/10.1109/ICDSP.2018.8631857","url":null,"abstract":"Data-driven false data injection attack is one of the emerging techniques in smart grids, provided that the adversary can monitor the meter readings. The basic idea is constructing attack vectors from the estimated signal subspace, without knowing system measurement matrix. However, its stealthy performance is significantly influenced by the accuracy of the estimated subspace. Furthermore, it is computationally demanding, because full-size singular value decomposition (SVD) is required for model order selection. In this paper, we propose a truncated SVD based computationally efficient attacking scheme using only the first dominant eigenvector. Both experiment and simulation results are provided to evaluate the performance of the proposed scheme. Compared with the standard false data injection techniques with known measurement matrix, similar stealthy performance is achieved with a reasonable computational complexity.","PeriodicalId":218806,"journal":{"name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132248425","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: 8
Robust Constrained Recursive Least P-Power Algorithm for Adaptive Filtering 鲁棒约束递归最小p幂自适应滤波算法
2018 IEEE 23rd International Conference on Digital Signal Processing (DSP) Pub Date : 2018-11-01 DOI: 10.1109/ICDSP.2018.8631663
Jiajun Sun, Siyuan Peng, Qinglai Liu, Ruijie Zhao, Zhiping Lin
{"title":"Robust Constrained Recursive Least P-Power Algorithm for Adaptive Filtering","authors":"Jiajun Sun, Siyuan Peng, Qinglai Liu, Ruijie Zhao, Zhiping Lin","doi":"10.1109/ICDSP.2018.8631663","DOIUrl":"https://doi.org/10.1109/ICDSP.2018.8631663","url":null,"abstract":"In this paper, we develop a novel constrained adaptive filtering algorithm called constrained recursive least p-power (CRLP) algorithm, which incorporates a set of linear constraints into the least mean p-power error (LMP) criterion to solve a constrained optimization problem directly. Compared with the conventional constrained adaptive filtering algorithms including constrained least mean square (CLMS), constrained recursive least square (CRLS) and constrained least mean p-power (CLMP), CRLP can achieve better performance under non- Gaussian noises. Simulation results are presented to confirm the superior performance of the new algorithm.","PeriodicalId":218806,"journal":{"name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127997971","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
FPGA-based Baseband Solution for High Performance Industrial Wireless Communication 基于fpga的高性能工业无线通信基带解决方案
2018 IEEE 23rd International Conference on Digital Signal Processing (DSP) Pub Date : 2018-11-01 DOI: 10.1109/ICDSP.2018.8631662
Mingjie Hao, Ludwig Karsthof, Jochen Rust, Johannes Demel, C. Bockelmann, A. Dekorsy, Ahmad Al Houry, Fabian Mackenthun, S. Paul
{"title":"FPGA-based Baseband Solution for High Performance Industrial Wireless Communication","authors":"Mingjie Hao, Ludwig Karsthof, Jochen Rust, Johannes Demel, C. Bockelmann, A. Dekorsy, Ahmad Al Houry, Fabian Mackenthun, S. Paul","doi":"10.1109/ICDSP.2018.8631662","DOIUrl":"https://doi.org/10.1109/ICDSP.2018.8631662","url":null,"abstract":"Recently, the wireless commuication system development driven by the ongoing Industry 4.0 (I40) and Indusrial Internet of Thing (IIoT) has been growing enormously. In industrial automation and manufacturing, closed-loop control applications are commonly used, which require completely new solutions to achieve latencies of 1ms with extremely high reliability and stringent requirements on message timing and repetitive packet losses. A hardware-based solution for baseband signal processing aiming at such challenges is introduced in this work. With a novel design and integration of the baseband signal processing blocks, the key highlights of this solution are a) multi-user support, b) simple and flexible integration in the industrial application, c) low hardware overhead, and d) high data throughput with low latency.","PeriodicalId":218806,"journal":{"name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128695939","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: 7
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