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检索条件"任意字段=2008 IEEE Sensor Array and Multichannel Signal Processing Workshop"

共 1267 条记录，以下是121-130 订阅

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Optimal Angular sensor Separation for DRSS Localization

Optimal Angular Sensor Separation for DRSS Localization

引用

sensor array and multichannel signal processing workshop

作者： Jun Li Kutluyı l Doğ anç ay Hatem Hmam UniSA STEM University of South Australia Cyber and ElectronicWarfare Division Defence Science &#x0026 Technology Group

This paper investigates optimal target-sensor geometries for differential received signal strength (DRSS) localization in the 2D-plane. To achieve this, the D-optimality criterion is employed, which maximizes the determinant of the Fisher information matrix (FIM). We observe that equiangular sensor separation maximizes the determinant of the FIM, forming the best geometry, for equal target -sensor ranges under the assumption of identical log-normal noise variances for all sensor measurements. However, when the distances between the target and sensors are different, equiangular sensor separation cannot meet the optimal geometry condition. We provide analytical and numerical solutions for optimal geometries for the specific cases of three and four sensors with non-uniform target-sensor ranges.

关键词： Geometry Location awareness sensor placement Maximum likelihood estimation Numerical analysis array signal processing Conferences

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Building Large Models from Small Distributed Models: A Layer Matching Approach

Building Large Models from Small Distributed Models: A Layer...

引用

sensor array and multichannel signal processing workshop

作者： Xinwei Zhang Bingqing Song Mehrdad Honarkhah Jie Dingl Mingyi Hong University of Minnesota Facebook Meta Platforms Inc.

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Cross-device federated learning (FL) has emerged as a promising approach to leverage the collective power of numerous clients for training machine learning models using their local data and computational resources. Meanwhile, huge models have recently been developed to fully utilize such a large amount of data and achieve high performance on various tasks. However, training such large models requires substantial storage and computational resources, and resource limitations of the individual client devices in the FL systems often prevent the utilization of large modern deep learning models. In this paper, we address this challenge by proposing a novel federated layer matching (FLM) algorithm that enables the server to construct a deep server model by leveraging relatively shallow client models. The FLM algorithm dynamically matches and combines similar layers from the client models into the server model while incorporating dissimilar layers as new layers. By employing this strategy, clients can train smaller models that align with their device capacities, while the server can aggregate and derive a larger, more powerful server model by leveraging the distributed client data. Our empirical results demonstrate that the FLM algorithm enables the construction of a server model that is significantly larger than the individual client models, and the server model matches the performance of the same-sized model trained in the centralized setting. Further, the model constructed by FLM significantly outperforms the model obtained using the classical model averaging algorithm under the same amount of communication and client computational resources.

关键词： Training Performance evaluation Federated learning Computational modeling Heuristic algorithms signal processing algorithms Data models

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Blind Source Separation with Non-Coplanar Interferometric Data

Blind Source Separation with Non-Coplanar Interferometric Da...

引用

sensor array and multichannel signal processing workshop

作者： Ré mi Carloni Gertosio Jé rô me Bobin IRFU CEA Universit&#x00E9 Paris-Saclay Gif-sur-Yvette France

The advent of large-scale radio-interferometers mandates the development of new analysis methods that can tackle instrumental effects such as antenna baseline non-coplanarity. In particular, blind source separation (BSS) methods, which are one of the main analytical tools for extracting valuable physical information from the multispectral data provided by radio-interferometers, must be adapted. To that end, we intro-duce a joint deconvolution and blind source separation (DBSS) algorithm called wGMCA, allowing the analysis of non-coplanar interferometric data in radio-astronomy.

关键词： Deconvolution Image resolution Instruments Conferences signal processing algorithms Blind source separation Data mining

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Decision Fusion for Carbon Dioxide Release Detection from Pressure Relief Devices

Decision Fusion for Carbon Dioxide Release Detection from Pr...

引用

sensor array and multichannel signal processing workshop

作者： Gianluca Tabella Yuri Di Martino Domenico Ciuonzo Nicola Paltrinieri Xiaodong Wang Pierluigi Salvo Rossi Dept. Electronic Systems Norwegian University of Science and Technology Trondheim Norway Dept. Electrical Engineering Columbia University New York NY USA Dept. Electrical Engineering and Information Technologies (DIETI) University of Naples &#x201C Federico II&#x201D Naples Italy Dept. Mechanical and Industrial Engineering Norwegian University of Science and Technology Trondheim Norway Dept. Gas Technology SINTEF Energy Research Norway

This work investigates the distributed detection of carbon dioxide (CO 2 ) release from storage tanks caused by the opening of pressure relief devices via inexpensive sensor devices in an industrial context. A realistic model of the dispersion is put forward in this paper. Both full-precision and rate-limited setups for sensors are considered, and fusion rules capitalizing the dis-persion model are derived. Simulations analyze the performance trends with relevant system parameters.

关键词： Performance evaluation Analytical models array signal processing Conferences Carbon dioxide Market research Carbon

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How Should IRSs Scale to Harden Multi-Antenna Channels?

How Should IRSs Scale to Harden Multi-Antenna Channels?

引用

sensor array and multichannel signal processing workshop

作者： Ali Bereyhi Saba Asaad Chongjun Ouyang Ralf R. Mü ller Rafael F. Schaefer H. Vincent Poor Friedrich-Alexander Universit&#x00E4 t Erlangen-N&#x00FC rnberg (FAU) Beijing University of Posts and Telecommunications University of Siegen Princeton University

This work extends the concept of channel hardening to multi-antenna systems that are aided by intelligent reflecting surfaces (IRSs). For fading links between a multi-antenna transmitter and a single-antenna receiver, we derive an accurate approximation for the distribution of the input-output mutual information when the number of reflecting elements grows large. The asymptotic results demonstrate that by increasing the number of elements on the IRS, the end-to-end channel hardens as long as the physical dimensions of the IRS grow as well. The growth rate however need not to be of a specific order and can be significantly sub-linear. The validity of the analytical result is confirmed by numerical experiments.

关键词： Fading channels Transmitters array signal processing Conferences Receivers Surface treatment Mutual information

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HIGH-RESOLUTION TARGET SENSING USING MULTI-FREQUENCY SPARSE array 11

HIGH-RESOLUTION TARGET SENSING USING MULTI-FREQUENCY SPARSE ...

引用

ieee 11th sensor array and multichannel signal processing workshop (SAM)

作者： Ahmed, Ammar Silage, Dennis Zhang, Yimin D. Temple Univ Dept Elect & Comp Engn Philadelphia PA 19122 USA

ISBN: (纸本)9781728119465

In this paper, we discuss high-resolution target sensing through the exploitation of multi-frequency sparse array processing. By using simple design examples of a three-element sensor array coupled with the sensing signals consisting of three well-designed frequencies, we provide insights to achieve a high number of consecutive lags, unique lags, and array aperture. Such multi-frequency sensor arrays with reduced number of sensors can be attractive in many applications to achieve effective sensing with a low cost.

关键词： Sparse array multi-frequency sensing group sparsity DOA estimation

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DoA Estimation Performance of UCAs with Reduced Number of sensors using Phase-Mode Transformation and Small Sample Support

DoA Estimation Performance of UCAs with Reduced Number of Se...

引用

sensor array and multichannel signal processing workshop

作者： Guilherme Murmel Liali José A. Apoliná rio Marcello L. R. De Campos Antonio L. L. Ramos Dept. Defense Military Institute of Engineering Rio de Janeiro Brazil Dept. Electrical Engineering Military Institute of Engineering Rio de Janeiro Brazil Prog. Electrical Engineering Federal Univ. of Rio de Janeiro Rio de Janeiro Brazil Dept. Science and Industry Systems University of South-Eastern Norway Kongsberg Norway

In this work, we assess the performance of a Uniform Circular array featuring a reduced number of sensors and using small sample support comprised of only a few snapshots. We begin by analyzing the limitations of the phase-mode transformation in the context of a uniform circular array with a reduced number of sensors. Next, we address the challenging issue of having limited sample support, followed by a brief discussion of the techniques that can be used to mitigate the degradation caused by the two aforementioned problems. Several experiments are conducted to evaluate the DoA estimation performance of narrowband acoustic signals in different scenarios, having water as propagating media.

关键词： Phased arrays Degradation Direction-of-arrival estimation array signal processing Conferences Estimation Media

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Computation of Weight Function of 2qth Order Virtual array to Analyse the Estimation Performance 11

Computation of Weight Function of 2qth Order Virtual Array t...

引用

ieee 11th sensor array and multichannel signal processing workshop (SAM)

作者： Gupta, Payal Agrawal, Monika Indian Inst Technol Ctr Appl Res Elect New Delhi 110016 India

ISBN: (纸本)9781728119465

Increasing the number of sources to be processed from a given array of sensors is an important problem in sensor array signal processing and of interest to many researchers. This problem has also been tackled with the virtual array based approach where the covariance and cumulant lags provide a virtual sensor. Here, an important parameter which affects the parameter estimation accuracy and latency is weight function. The weight function is defined as the frequency of occurrence of each virtual sensor in the virtual array. We provide the close-form expression of virtual array corresponding to linear array. We have also analytically evaluated the weight function of virtual array and have also studied the effect of the weight function on parameter estimation. Simulation results show the parameter estimation accuracy is significantly improve with high weight function.

关键词： DoA estimation Non-circular signals Sparse array Virtual array Cumulants Underdetermined System Weight function Covariance Matrix

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Moving target detection of array antennas based on time reversal 11

Moving target detection of array antennas based on time reve...

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ieee 11th sensor array and multichannel signal processing workshop (SAM)

作者： Zhang, Zhaoming Chen, Baixiao Yang, Minglei Xu, Hui Xidian Univ Natl Lab Radar Signal Proc Xian Peoples R China Xidian Univ Sch Elect Engn Xian Peoples R China

ISBN: (纸本)9781728119465

This paper develops a time reversal moving target detector based on array antennas. Time reversal utilizes the multipath effect by retransmitting the received signal containing the Doppler shift of the moving target. Two detectors are derived in both conventional and time reversal scenarios, respectively. The Monte Carlo results show that the time reversal detector significantly improves the target detection probability in multipath environments compared with the conventional detector. The increase of multipath number is helpful to improve the detection probability of time reversal detector.

关键词： time reversal moving target array antennas detection

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DOA ESTIMATION EXPLOITING INTERPOLATED MULTI-FREQUENCY SPARSE array 11

DOA ESTIMATION EXPLOITING INTERPOLATED MULTI-FREQUENCY SPARS...

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ieee 11th sensor array and multichannel signal processing workshop (SAM)

作者： Zhang, Shuimei Ahmed, Ammar Zhang, Yimin D. Sun, Shunqiao Temple Univ Dept Elect & Comp Engn Philadelphia PA 19122 USA Univ Alabama Dept Elect & Comp Engn Tuscaloosa AL USA

ISBN: (纸本)9781728119465

We consider gridless direction-of-arrival (DOA) estimation of much more targets than the number of physical sensors through the exploitation of multi-frequency sparse array design and processing which increase the degrees of freedom as more frequency components are used. A modified sensor interpolation technique is developed to accurately estimate the signal covariance matrix using very few snapshots, thereby eliminating the requirement of a large number of snapshots as in conventional different coarray-based DOA estimation. Simulation results demonstrate high-resolution gridless DOA estimation capability of more targets than the number of physical sensors.

关键词： Sparse array multi-frequency sensing array interpolation direction-of-arrival estimation

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