Eurasip Journal on Advances in Signal Processing最新文献_第4页

A comparative study of multiple neural network for detection of COVID-19 on chest X-ray. 多重神经网络检测胸部 X 光片上 COVID-19 的比较研究。

IF 1.9 4区工程技术

Eurasip Journal on Advances in Signal Processing Pub Date : 2021-01-01 Epub Date: 2021-07-27 DOI: 10.1186/s13634-021-00755-1

Anis Shazia, Tan Zi Xuan, Joon Huang Chuah, Juliana Usman, Pengjiang Qian, Khin Wee Lai

{"title":"A comparative study of multiple neural network for detection of COVID-19 on chest X-ray.","authors":"Anis Shazia, Tan Zi Xuan, Joon Huang Chuah, Juliana Usman, Pengjiang Qian, Khin Wee Lai","doi":"10.1186/s13634-021-00755-1","DOIUrl":"10.1186/s13634-021-00755-1","url":null,"abstract":"Coronavirus disease of 2019 or COVID-19 is a rapidly spreading viral infection that has affected millions all over the world. With its rapid spread and increasing numbers, it is becoming overwhelming for the healthcare workers to rapidly diagnose the condition and contain it from spreading. Hence it has become a necessity to automate the diagnostic procedure. This will improve the work efficiency as well as keep the healthcare workers safe from getting exposed to the virus. Medical image analysis is one of the rising research areas that can tackle this issue with higher accuracy. This paper conducts a comparative study of the use of the recent deep learning models (VGG16, VGG19, DenseNet121, Inception-ResNet-V2, InceptionV3, Resnet50, and Xception) to deal with the detection and classification of coronavirus pneumonia from pneumonia cases. This study uses 7165 chest X-ray images of COVID-19 (1536) and pneumonia (5629) patients. Confusion metrics and performance metrics were used to analyze each model. Results show DenseNet121 (99.48% of accuracy) showed better performance when compared with the other models in this study.","PeriodicalId":49203,"journal":{"name":"Eurasip Journal on Advances in Signal Processing","volume":"2021 1","pages":"50"},"PeriodicalIF":1.9,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8314263/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39264618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Stationary time-vertex signal processing. 平稳时间-顶点信号处理。

IF 1.9 4区工程技术

Eurasip Journal on Advances in Signal Processing Pub Date : 2019-01-01 Epub Date: 2019-08-20 DOI: 10.1186/s13634-019-0631-7

Andreas Loukas, Nathanaël Perraudin

引用次数: 40

Superimposed signaling inspired channel estimation in full-duplex systems. 全双工系统中受叠加信号启发的信道估计。

IF 1.9 4区工程技术

Eurasip Journal on Advances in Signal Processing Pub Date : 2018-01-01 Epub Date: 2018-01-24 DOI: 10.1186/s13634-018-0529-9

Abbas Koohian, Hani Mehrpouyan, Ali A Nasir, Salman Durrani, Steven D Blostein

{"title":"Superimposed signaling inspired channel estimation in full-duplex systems.","authors":"Abbas Koohian, Hani Mehrpouyan, Ali A Nasir, Salman Durrani, Steven D Blostein","doi":"10.1186/s13634-018-0529-9","DOIUrl":"https://doi.org/10.1186/s13634-018-0529-9","url":null,"abstract":"Residual self-interference (SI) cancellation in the digital baseband is an important problem in full-duplex (FD) communication systems. In this paper, we propose a new technique for estimating the SI and communication channels in a FD communication system, which is inspired from superimposed signaling. In our proposed technique, we add a constant real number to each constellation point of a conventional modulation constellation to yield asymmetric shifted modulation constellations with respect to the origin. We show mathematically that such constellations can be used for bandwidth efficient channel estimation without ambiguity. We propose an expectation maximization (EM) estimator for use with the asymmetric shifted modulation constellations. We derive a closed-form lower bound for the mean square error (MSE) of the channel estimation error, which allows us to find the minimum shift energy needed for accurate channel estimation in a given FD communication system. The simulation results show that the proposed technique outperforms the data-aided channel estimation method, under the condition that the pilots use the same extra energy as the shift, both in terms of MSE of channel estimation error and bit error rate. The proposed technique is also robust to an increasing power of the SI signal.","PeriodicalId":49203,"journal":{"name":"Eurasip Journal on Advances in Signal Processing","volume":"2018 1","pages":"8"},"PeriodicalIF":1.9,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13634-018-0529-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37579841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Joint frequency offset, time offset, and channel estimation for OFDM/OQAM systems. 联合频率偏移，时间偏移和信道估计OFDM/OQAM系统。

IF 1.9 4区工程技术

Eurasip Journal on Advances in Signal Processing Pub Date : 2018-01-01 Epub Date: 2018-01-08 DOI: 10.1186/s13634-017-0526-4

Ali Baghaki, Benoit Champagne

{"title":"Joint frequency offset, time offset, and channel estimation for OFDM/OQAM systems.","authors":"Ali Baghaki, Benoit Champagne","doi":"10.1186/s13634-017-0526-4","DOIUrl":"https://doi.org/10.1186/s13634-017-0526-4","url":null,"abstract":"Among the multicarrier modulation techniques considered as an alternative to orthogonal frequency division multiplexing (OFDM) for future wireless networks, a derivative of OFDM based on offset quadrature amplitude modulation (OFDM/OQAM) has received considerable attention. In this paper, we propose an improved joint estimation method for carrier frequency offset, sampling time offset, and channel impulse response, needed for the practical application of OFDM/OQAM. The proposed joint ML estimator instruments a pilot-based maximum-likelihood (ML) estimation of the unknown parameters, as derived under the assumptions of Gaussian noise and independent input symbols. The ML estimator formulation relies on the splitting of each received pilot symbol into contributions from surrounding pilot symbols, non-pilot symbols and additive noise. Within the ML framework, the Cramer-Rao bound on the covariance matrix of unbiased estimators of the joint parameter vector under consideration is derived as a performance benchmark. The proposed method is compared with a highly cited previous work. The improvements in the results point to the superiority of the proposed method, which also performs close to the Cramer-Rao bound.","PeriodicalId":49203,"journal":{"name":"Eurasip Journal on Advances in Signal Processing","volume":"2018 1","pages":"4"},"PeriodicalIF":1.9,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13634-017-0526-4","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37593490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Computable performance guarantees for compressed sensing matrices. 压缩传感矩阵的可计算性能保证

IF 1.9 4区工程技术

Eurasip Journal on Advances in Signal Processing Pub Date : 2018-01-01 Epub Date: 2018-02-27 DOI: 10.1186/s13634-018-0535-y

Myung Cho, Kumar Vijay Mishra, Weiyu Xu

引用次数: 0

Fast dictionary learning from incomplete data. 快速字典学习从不完整的数据。

IF 1.9 4区工程技术

Eurasip Journal on Advances in Signal Processing Pub Date : 2018-01-01 Epub Date: 2018-02-22 DOI: 10.1186/s13634-018-0533-0

Valeriya Naumova, Karin Schnass

{"title":"Fast dictionary learning from incomplete data.","authors":"Valeriya Naumova, Karin Schnass","doi":"10.1186/s13634-018-0533-0","DOIUrl":"10.1186/s13634-018-0533-0","url":null,"abstract":"This paper extends the recently proposed and theoretically justified iterative thresholding and K residual means (ITKrM) algorithm to learning dictionaries from incomplete/masked training data (ITKrMM). It further adapts the algorithm to the presence of a low-rank component in the data and provides a strategy for recovering this low-rank component again from incomplete data. Several synthetic experiments show the advantages of incorporating information about the corruption into the algorithm. Further experiments on image data confirm the importance of considering a low-rank component in the data and show that the algorithm compares favourably to its closest dictionary learning counterparts, wKSVD and BPFA, either in terms of computational complexity or in terms of consistency between the dictionaries learned from corrupted and uncorrupted data. To further confirm the appropriateness of the learned dictionaries, we explore an application to sparsity-based image inpainting. There the ITKrMM dictionaries show a similar performance to other learned dictionaries like wKSVD and BPFA and a superior performance to other algorithms based on pre-defined/analytic dictionaries.","PeriodicalId":49203,"journal":{"name":"Eurasip Journal on Advances in Signal Processing","volume":"2018 1","pages":"12"},"PeriodicalIF":1.9,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13634-018-0533-0","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35882807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

Position estimation with a millimeter-wave massive MIMO system based on distributed steerable phased antenna arrays. 基于分布式可控相控阵的毫米波海量MIMO系统位置估计。

IF 1.9 4区工程技术

Eurasip Journal on Advances in Signal Processing Pub Date : 2018-01-01 Epub Date: 2018-06-05 DOI: 10.1186/s13634-018-0553-9

Nenad Vukmirović, Miloš Janjić, Petar M Djurić, Miljko Erić

{"title":"Position estimation with a millimeter-wave massive MIMO system based on distributed steerable phased antenna arrays.","authors":"Nenad Vukmirović, Miloš Janjić, Petar M Djurić, Miljko Erić","doi":"10.1186/s13634-018-0553-9","DOIUrl":"https://doi.org/10.1186/s13634-018-0553-9","url":null,"abstract":"In this paper, we propose a massive MIMO (multiple-input-multiple-output) architecture with distributed steerable phased antenna subarrays for position estimation in the mmWave range. We also propose localization algorithms and a multistage/multiresolution search strategy that resolve the problem of high side lobes, which is inherent in spatially coherent localization. The proposed system is intended for use in line-of-sight indoor environments. Time synchronization between the transmitter and the receiving system is not required, and the algorithms can also be applied to a multiuser scenario. The simulation results for the line-of-sight-only and specular multipath scenarios show that the localization error is only a small fraction of the carrier wavelength and that it can be achieved under reasonable system parameters including signal-to-noise ratios, antenna number/placement, and subarray apertures. The proposed concept has the potential of significantly improving the capacity and spectral/energy efficiency of future mmWave massive MIMO systems.","PeriodicalId":49203,"journal":{"name":"Eurasip Journal on Advances in Signal Processing","volume":"2018 1","pages":"33"},"PeriodicalIF":1.9,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13634-018-0553-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36223997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

Joint source and relay optimization for interference MIMO relay networks. 干扰MIMO中继网络的联合源与中继优化。

IF 1.9 4区工程技术

Eurasip Journal on Advances in Signal Processing Pub Date : 2017-01-01 Epub Date: 2017-03-07 DOI: 10.1186/s13634-017-0453-4

Muhammad R A Khandaker, Kai-Kit Wong

引用次数: 6

MapReduce particle filtering with exact resampling and deterministic runtime. MapReduce粒子滤波与精确的重采样和确定性的运行时。

IF 1.9 4区工程技术

Eurasip Journal on Advances in Signal Processing Pub Date : 2017-01-01 Epub Date: 2017-10-18 DOI: 10.1186/s13634-017-0505-9

Jeyarajan Thiyagalingam, Lykourgos Kekempanos, Simon Maskell

{"title":"MapReduce particle filtering with exact resampling and deterministic runtime.","authors":"Jeyarajan Thiyagalingam, Lykourgos Kekempanos, Simon Maskell","doi":"10.1186/s13634-017-0505-9","DOIUrl":"https://doi.org/10.1186/s13634-017-0505-9","url":null,"abstract":"Particle filtering is a numerical Bayesian technique that has great potential for solving sequential estimation problems involving non-linear and non-Gaussian models. Since the estimation accuracy achieved by particle filters improves as the number of particles increases, it is natural to consider as many particles as possible. MapReduce is a generic programming model that makes it possible to scale a wide variety of algorithms to Big data. However, despite the application of particle filters across many domains, little attention has been devoted to implementing particle filters using MapReduce. In this paper, we describe an implementation of a particle filter using MapReduce. We focus on a component that what would otherwise be a bottleneck to parallel execution, the resampling component. We devise a new implementation of this component, which requires no approximations, has O(N) spatial complexity and deterministic O((logN)2) time complexity. Results demonstrate the utility of this new component and culminate in consideration of a particle filter with 224 particles being distributed across 512 processor cores.","PeriodicalId":49203,"journal":{"name":"Eurasip Journal on Advances in Signal Processing","volume":"2017 1","pages":"71"},"PeriodicalIF":1.9,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s13634-017-0505-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37603016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

A novel aliasing-free subband information fusion approach for wideband sparse spectral estimation. 宽带稀疏谱估计中一种新的无混叠子带信息融合方法。

IF 1.9 4区工程技术

Eurasip Journal on Advances in Signal Processing Pub Date : 2017-01-01 Epub Date: 2017-08-23 DOI: 10.1186/s13634-017-0494-8

Ji-An Luo, Xiao-Ping Zhang, Zhi Wang

引用次数: 4