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检索条件"任意字段=Conference on Signal and Data Processing of Small Targets"

共 9214 条记录，以下是4671-4680 订阅

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A COMPRESSIVE SENSING APPROACH TO THE FUSION OF PCL SENSORS

A COMPRESSIVE SENSING APPROACH TO THE FUSION OF PCL SENSORS

引用

21st European signal processing conference (EUSIPCO)

作者： Ender, Joachim H. G. Fraunhofer FHR D-53343 Wachtberg Germany

ISBN: (纸本)9781479936878

Sensor data fusion techniques have been applied in the recent years to the combination of the information provided by different sensor systems. Passive coherent location (PCL) networks use the illumination by common radio or television transmitters to detect air-targets and estimate their positions and parameters due to the reflected waves. To fuse the information of the bistatic Tx-Rx pairs advanced techniques have been developed based on the detections and parameter estimates obtained at each bistatic pair. In our paper we will consider joined signal processing of the radar raw data based on compressive sensing (CS) techniques using the block-sparsity approach.

关键词： Compressive sensing data fusion Block-sparsity Passive coherent location MIMO radar airspace surveillance

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Inference of tumor inhibition pathways from drug perturbation data

Inference of tumor inhibition pathways from drug perturbatio...

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IEEE Global conference on signal and Information processing (GlobalSIP)

作者： Haider, Saad Pal, Ranadip Texas Tech Univ Dept Elect & Comp Engn Lubbock TX 79409 USA

ISBN: (纸本)9781479902484

The tumor proliferation pathways for each individual patient encompass variations and a successful treatment regime based on targeted drugs necessitates the estimation of the influences of target inhibition on cell viability. In this article, we consider an inference approach to decipher the significant blocks of protein targets and the effect of their inhibition on tumor proliferation. Our framework is based on sequential search and non-linear optimization for estimating the block parameters. The proposed algorithm is tested on extensive synthetic data and provides high accuracy estimates for model parameters. We furthermore evaluated the performance of the framework in presence of noise and were able to achieve high precision cell viability prediction.

关键词： Parameter estimation

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S-band radar based on Lyrtech Software Defined Radio

S-band radar based on Lyrtech Software Defined Radio

引用

IEEE National conference on Aerospace and Electronics (NAECON)

作者： Siyang Cao Yuan F. Zheng Robert L. Ewing Department of Electrical and Computer Engineering The Ohio State University Columbus Ohio Sensors Directorate US Air Force Research Laboratory Wright-Patterson Air Force Base Ohio

The focus of this paper is on the development of Sband radar using the Lyrtech small Form Factor (SFF) Software Defined Radio (SDR) for generating the Chirp-Z signal. The Lyrtech SDR platform has a high speed AD/DA conversion board and a tunable RF board, which enable a flexible radar design. To achieve a functional radar system, the development kids of the SFF SDR have to be fully utilized. This paper introduces the usage of both software and hardware resources of the SDR for converting the SDR into a waveform-programmable radar, which can benefit the study of radar systems using generic SDR platforms. Based on our approach, we develop an S-band radar which is used to transmit a Chirp-Z radar waveform modulated on a 2.2GHz carrier. The structure and the development kits of the SFF platform are introduced, and the development of the S-band radar by using the development kits discussed. Finally, both transmitted and received Chirp-Z signals using the developed radar system are demonstrated.

关键词： Radar Digital signal processing Field programmable gate arrays Software Radio frequency Real-time systems data conversion

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NEURAL DECODING OF MOVEMENT targets BY UNSORTED SPIKE TRAINS

NEURAL DECODING OF MOVEMENT TARGETS BY UNSORTED SPIKE TRAINS

引用

IEEE International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Xu, Zhiming Ang, Kai Keng Guan, Cuntai ASTAR Inst Infocomm Res Singapore 138632 Singapore

ISBN: (纸本)9781479903566

Decoding movement targets from neural activity in motor cortex using invasive brain-computer interface (BCI) has potential application to help disabled patients. Most works employed spike sorting to obtain the single units (SUs) for decoding from the extracellular electrode recordings. However, spike sorting is difficult, computational demanding, and is often limited by the spike waveform variability especially in low SNR and high neuronal density conditions. To address these issues, we proposed a decoding method using unsorted spike trains from recording electrodes based on the maximal likelihood (ML) estimation approach. An experiment was performed to test neuronal data recorded from a rhesus monkey performing the center-out movement task of eight targets. The results showed that the proposed method yielded average correct decoding rate of 98.5% compared to the SU based method that yielded correct decoding rate of 96.3%. The results also showed that the proposed method yielded improved computational efficiency. Thus the proposed method showed potential for real time BCI applications with large scale of neuronal recordings.

关键词： Brain computer interface maximal likelihood motor cortex neural decoding Poisson distribution

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Massive MIMO for mmWave systems

Massive MIMO for mmWave systems

引用

Asilomar conference on signals, Systems & Computers

作者： Frederick W. Vook Timothy A. Thomas Eugene Visotsky Nokia Networks Arlington Heights IL USA

The large bandwidths available at the millimeter wave (mmWave) carrier frequencies (e.g., 30-100 GHz) have sparked significant interest in developing cellular systems in those bands to meet the ever-increasing demand for high data rates. Large-scale antenna arrays with tens or hundreds of antennas are envisioned to be a prerequisite for operating in the mmWave bands due to the poor path loss conditions in those bands. Previous studies for 72GHz carrier frequencies have shown how extremely high data rates can be achieved in ultra-dense small cell deployments through simple single-user MIMO techniques mainly by virtue of the high system bandwidth (on the order of 1-2GHz). In this paper, we extend the prior work on single-user MIMO (SU-MIMO) for mmWave bands and examine the question of whether Multi-User MIMO (MU-MIMO) is a useful approach for mmWave bands. We show that there are definite cases where MU-MIMO can provide significant system capacity gains over SU-MIMO in the mmWave bands, which is in contrast to the expectation that the poor path loss conditions necessitate simple high gain beamforming techniques. We show that in many cases, a large-scale array provides sufficient SINR gain that can enable further gains from multi-user spatial multiplexing. We show how those gains depend on a variety of factors such as the user density and the transmission strategy.

关键词： Interference MIMO Throughput Antenna arrays signal to noise ratio Bandwidth Array signal processing

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Real-time implementation and evaluation of an adaptive energy-aware data compression for wireless EEG monitoring systems

Real-time implementation and evaluation of an adaptive energ...

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International conference on Quality of Service in Heterogeneous Wired/Wireless Networks (QSHINE)

作者： Alaa Awad Medhat Hamdy Amr Mohamed Hussein Alnuweiri Department of Computer Science Qatar University Doha Qatar Department of Electrical and Computer Engineering Texas A&M University Doha Qatar

ISBN: (纸本)9781479940363

Wireless sensor technologies can provide the leverage needed to enhance patient-caregivers collaboration through ubiquitous access and direct communication, which promotes smart and scalable vital sign monitoring of the chronically ill and elderly people live an independent life. However, the design and operation of BASNs are challenging, because of the limited power and small form factor of biomedical sensors. In this paper, an adaptive compression technique that aims at achieving low-complexity energy-efficient compression subject to time delay and distortion constraints is proposed. In particular, we analyze the processing energy consumption, then an energy consumption optimization model with constraints of distortion and time delay is proposed. Using this model, the Personal data Aggregator (PDA) dynamically chooses the optimal compression parameters according to real-time measurements of the packet delivery ratio (PDR) or individual users. To evaluate and verify our optimization model, we develop an experimental testbed, where the EEG data is sent to the PDA that compresses the gathered data and forwards it to the server which decompresses and reconstructs the original signal. Experimental testbed and simulation results show that our adaptive compression technique can offer significant savings in the delivery time with low complexity and without affecting application accuracies.

关键词： Servers Optimization Electroencephalography Brain modeling Delays Energy consumption Encoding

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Tomographic SAR Inversion by Generic Log-Barrier Algorithm: The Second Order Cone Programming Approach

Tomographic SAR Inversion by Generic Log-Barrier Algorithm: ...

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conference on SAR Image Analysis, Modeling, and Techniques XIII

作者： Biondi, Filippo Ciotti, Piero Pierdicca, Nazzareno Univ Aquila Dipartimento Ingn Ind & Informaz Econ Nucleo Ind Pile Via Giovanni Gronchi 18 I-67100 Laquila Italy

ISBN: (纸本)9780819497604

In Multi-Baseline SAR tomography it is necessary to process the acquired data by advanced signal processing techniques in order to adequately compensate the bad consequences of an under-sampled configuration. These techniques have to properly work on an environment characterized to have point targets, distributed targets and both of theme. This paper considers the Convex Optimization (CVX) tomographic solution in order to process multi-baseline data-sets collected in a Fourier under-sampled configuration in the above mentioned environment. The CVX and the Second Order Cone Programming Solution (SOCPs) have been tested by a generic log-barrier algorithm, through a successfully computational bottleneck Newton calculation. These techniques are validated on point targets, distributed targets and realistic forested environments.

关键词： Tomography signal processing Synthetic aperture radar Computer programming Detection and tracking algorithms data processing Radar data acquisition Device simulation Environmental sensing

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Detection of shallow buried objects using an autoregressive model on the ground penetrating radar signal

Detection of shallow buried objects using an autoregressive ...

引用

conference on Detection and Sensing of Mines, Explosive Objects, and Obscured targets XVIII

作者： Nabelek, Daniel P. Ho, K. C. Univ Missouri Dept Elect & Comp Engn Columbia MO 65211 USA

ISBN: (纸本)9780819495006

The detection of shallow buried low-metal content objects using ground penetrating radar (GPR) is a challenging task. This is because these targets are right underneath the ground and the ground bounce reflection interferes with their detections. They do not create distinctive hyperbolic signatures as required by most existing GPR detection algorithms due to their special geometric shapes and low metal content. This paper proposes the use of the Autoregressive (AR) modeling method for the detection of these targets. We fit an A-scan of the GPR data to an AR model. It is found that the fitting error will be small when such a target is present and large when it is absent. The ratio of the energy in an A-scan before and after AR model fitting is used as the confidence value for detection. We also apply AR model fitting over scans and utilize the fitting residual energies over several scans to form a feature vector for improving the detections. Using the data collected from a government test site, the proposed method can improve the detection of this kind of targets by 30% compared to the pre-screener, at a false alarm rate of 0.002/m(2).

关键词： Classification Ground Penetrating Radar signal processing

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Joint Along Track Interferometry and Space-Time Adaptive processing for Target Detection and Geolocation

Joint Along Track Interferometry and Space-Time Adaptive Pro...

引用

IEEE Radar conference (RADAR)

作者： Uysl, Faruk Murthy, Vinay Li, Ke Y. Pillai, S. Unnikrishnan Davis, Mark E. C&P Technol Inc Closter NJ 07624 USA Medavis Consulting Prospect Trenton NJ 13435 USA

ISBN: (纸本)9781467357944;9781467357920

This paper presents a new adaptive radar signal processing technique for target detection and geolocation using radar data from platforms capable of performing simultaneous Synthetic Aperture Radar (SAR) and Along-Track Interferometry (ATI). Space-Time Adaptive processing (STAP) and ATI processing methodologies are combined in parallel to simultaneously image, detect and identify the geolocation of moving targets over clutter using data obtained from a single set of measurements. Proposed method allows use of a common data source and interconnected methods to fully exploit the information content of the measured data for improved target detection and geolocation.

关键词： geophysical signal processing radar clutter radar detection radar interferometry radar signal processing radar tracking space-time adaptive processing synthetic aperture radar target tracking

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ANTIFORENSICS ATTACKS TO BENFORD'S LAW FOR THE DETECTION OF DOUBLE COMPRESSED IMAGES

ANTIFORENSICS ATTACKS TO BENFORD'S LAW FOR THE DETECTION OF ...

引用

IEEE International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Milani, Simone Tagliasacchi, Marco Tubaro, Stefano Politecn Milan DEI I-20133 Milan Italy

ISBN: (纸本)9781479903566

Researchers have been recently challenging the robustness of forensic algorithms by designing antiforensic strategies that try to fool them. In this paper, we propose an antiforensic strategy that targets double image compression detectors based on Benford's law (or first digit law). The proposed approach is able to modify the first digit statistics of the considered data (a double compressed image) to fool single/double compression detectors based on Benford's law. In this way, the proposed strategy tries to mimick the effects of a single compression with limited additional distortion. The presented algorithm performs better than previous state-of-the-art antiforensic strategies and can be easily extended to other fraud detection methods.

关键词： data compression digital forensics image coding object detection statistical analysis

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