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

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Evaluating the Performance to Detecting Topic Shift of Large Language Models: A Study 9

Evaluating the Performance to Detecting Topic Shift of Large...

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9th International conference on Intelligent Computing and signal processing, ICSP 2024

作者： Tian, Pingfang Liu, Deting Department of Computer Science and Technology Wuhan University of Science and Technology Wuhan430065 China Institute of Scientific and Technical Information of China The Key Laboratory of the Rich Media Knowledge Organisation and Service of Digital Publishing Content Beijing100038 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China Big Data Science and Engineering Research Institute Wuhan University of Science and Technology Wuhan430065 China

ISBN: (纸本)9798350376548

Topic shift detection aims to identify whether there is a change in the current topic of conversation or if a change is needed. The study found previous work did not evaluate the performance of large language models like ChatGPT on the task of topic shift. Therefore, this paper's main task and innovation lie in analyzing ChatGPT's performance on topic shift detection. To provide a more comprehensive evaluation, we conducted topic shift detection tasks on ChatGPT from three aspects: single utterances, adjacent utterances, and contextual levels. Additionally, to gauge the performance of large language models, we conducted experiments on multiple small-scale models and compared the results of the two models. Experimental results on the publicly available English TIAGE dataset showed that small-scale models exhibited lower recall in all three aspects, while ChatGPT performed better in the recall. This suggests that compared to small-scale models, large models are more capable of accurately detecting topic shifts. However, large models also exhibited lower precision, indicating that while ChatGPT can recognize content differences in utterances, its judgment on whether these different contents belong to the same topic is poor. © 2024 IEEE.

关键词： adjacent utterances level ChatGPT contextual level single utterances level topic shift detection

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Optimal frequencies and polarizations for radar detection of target

Optimal frequencies and polarizations for radar detection of...

引用

conference on Radar/Ladar processing and Applications

作者： YU, YJ ANDREA, T XU, F HUANG, SJ ALENIA SPAZIO SPA I-00131 ROMEITALY

ISBN: (纸本)0819419214

SAR radars create two-dimensional maps of terrain, each image pixel corresponding, uniquely, to a terrain resolution cell. Due to terrain inhomogeneity and SAR's inadequate resolution, some of the resolution cells may contain multiple elementary scatterers belonging to different classes. Radar returns from such a resolution cell are attributable to collective interaction of electromagnetric waves which are scattered by various kinds of elementary scatterers within the resolution cell. Simultaneous use of multispectral and polarimetric measurements at the pixel makes it possible to well decorrelate signals from different classes of elementary scatterers within corresponding resolution cell, facilitating the separation of different subpixel-sized elementary scatterers in each pixel. Frequency and polarization diversity offered by multifrequency and polarimetric SAR provids a method to tackle an important yet challenge task: detecting stationary man-made ground subpixel-sized targets from complex natural clutter. The objective of this investigation is to optimize frequencies and polarizations for detecting subpixel-sized target in clutter using multi-look, multifrequency polarimetric SAR data for a pixel. In the general targetplus-clutter versus clutter case, a general target detection model is established firstly. And then, based on this model, typical polarimetric covariance matrix parameters at several bands are used to illustrate the procedures of optimizing frequencies and polarizations for small target detection in clutter. © 1995 Proceedings of SPIE - The International Society for Optical Engineering. All rights reserved.

关键词： MULTIFREQUENCY POLARIMETRIC SAR data TARGET DETECTION

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GRIDLESS TOMOGRAPHIC SAR IMAGING BASED ON ACCELERATED ATOMIC NORM MINIMIZATION WITH EFFICIENCY

GRIDLESS TOMOGRAPHIC SAR IMAGING BASED ON ACCELERATED ATOMIC...

引用

2022 International conference on Radar Systems, RADAR 2022

作者： Gao, Silin Zhang, Zhe Zhang, Bingchen Wu, Yirong Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China Key Laboratory of Technology in Geo-spatial Information Processing and Application System Chinese Academy of Sciences Beijing100190 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Intelligent Aerospace Big Data Application Technology Suzhou215123 China Suzhou Aerospace Information Research Institute Suzhou215123 China

ISBN: (纸本)9781839537776

Synthetic aperture radar (SAR) tomography (TomoSAR) enables the reconstruction and three-dimensional (3D) localization of targets based on multiple two-dimensional (2D) observations of the same scene. The resolving along the elevation direction can be treated as a line spectrum estimation problem. However, traditional super-resolution spectrum estimation algorithms require multiple snapshots and uncorrelated targets. Meanwhile, as the most popular TomoSAR imaging method in modern years, compressed sensing (CS) based methods suffer from the gridding mismatch effect which markedly degrades the imaging performance. As a gridless CS approach, atomic norm minimization can avoid the gridding effect but requires enormous computing resources. Addressing the above issues, this paper proposes an improved fast ANM algorithm to TomoSAR elevation focusing by introducing the IVDST-ANM algorithm, which reduces the huge computational complexity of the conventional time-consuming semi-positive definite programming (SDP) by the iterative Vandermonde decomposition and shrinkage-thresholding (IVDST) approach, and retains the benefits of ANM in terms of gridless imaging and single snapshot recovery. We conducted experiments using simulated data to evaluate the performance of the proposed method, and reconstruction results of an urban area from the SARMV3D-Imaging 1.0 dataset are also presented. © 2022 IET conference Proceedings. All rights reserved.

关键词： Compressed sensing

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Radar signal processing using digital nonlinear filters

Radar signal processing using digital nonlinear filters

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

作者： D. Schleher F. Kozin AIL a division of CUTLER-HAMMER Deer Park N. Y. Cutler Hammer Inc. Deer Park NY USA

A fundamental digital signal processing technique is described that allows the synthesis of quasi-optimum nonlinear receivers for the detection of radar targets in clutter and noise. Methods for modeling radar signals as vector-Markov processes are described and compared with experimental data. Equations that describe an optimum receiver structure are derived. Approximate solutions for the optimum receiver equations are described and an algorithm suitable for digital implementation is given. A quasi-optimum nonlinear receiver for the detection of radar targets in correlated log-normal clutter and receiver noise is derived and its performance determined by simulating the resulting nonlinear digital receiver.

关键词： Radar signal processing Nonlinear filters signal processing Radar clutter signal processing algorithms signal design Markov processes Nonlinear equations Radar detection Process design

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UWB GPR for detection and identification of buried small objects

UWB GPR for detection and identification of buried small obj...

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conference on Radar Sensor Technology VIII and Passive Millimeter-Wave Imaging Technology VII

作者： Sahinkaya, DSA Turk, AS TUBITAK Marmara Res Ctr TR-41470 Gebze Kocaeli Turkey

ISBN: (纸本)0819453331

Recently considerable efforts are put in development of Ground Penetrating Radar (GPR) systems for detection and identification of the buried artifacts and structures. The GPR performance is associated with the proper-ties of the local soil and buried targets as well as the implementation of its hardware and software. When the aim in conventional GPR systems is detection of objects, some applications require identification of objects. It is necessary a new generation of GPR hardware for the identification of objects. This new hardware should perform highly accurate measurements of the scattered field. In this paper, the development of GPR system for the identification of buried small objects is presented. System covers broad bandwidth more than 2 GHz in order to achieve sufficient down-range resolution. GPR is operated lower frequencies because of technological restrictions of pulse generator. The performance of GPR for buried object detection and identification depends significantly on the ability of the antenna to radiate impulses into the ground without distortion. GPR antennas are operated close to the ground for efficiently coupling the energy into the ground. However this causes antenna characteristics to change as the ground condition changes. This characteristics instability makes it difficult to reduce the antenna clutter in the post processing. A novel broad band GPR antenna was developed over a wide frequency range to improve the stability. This new design was improved from dielectric loaded horn antenna.

关键词： Antennas General packet radio service Dielectrics Transmitters Receivers Transmission electron microscopy Amplifiers signal to noise ratio Radio propagation Sensors

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Process signal classification for aluminum cells

Process signal classification for aluminum cells

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conference on Intelligent Systems in Design and Manufacturing IV

作者： Banta, L Biedler, P Dai, C W Virginia Univ Morgantown WV 26506 USA

ISBN: (纸本)0819442933

The control of the aluminum reduction process is typically done based on measurements of cell voltage and current. Both signals are very noisy. Voltage fluctuations come from numerous sources such as CO, bubble generation, current fluctuations, metal pad motion, anode movement, electrical arcing, and changes in alumina concentration. The latter is an important control variable. but its effects on cell voltage are small and are often swamped by the signals from other sources. To date, control system designers have attempted to deal with this problem by extreme low-pass filtering and by suspension of all anode movements and alumina feed operations during the measurement period. This strategy is fairly effective, but leads in most cases to sub-optimal cell operation most of the time. Research at West Virginia University and Century Aluminum seeks to improve upon the traditional strategies by incorporating knowledge about the process and prior cell control actions in the data analysis operation. For example, selective bandpass filtering and model-based feature detection strategies can be used to identify, and isolate various portions of the composite signal. This paper discusses the methods being developed and the results of their application to this critical industrial process.

关键词： aluminum reduction cell control signal processing

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Mobile underwater acoustic communication with constantly changing Doppler effect

Mobile underwater acoustic communication with constantly cha...

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OCEANS - MTS/IEEE Kobe Techno-Oceans conference (OTO)

作者： Han, Xiao Ge, Wei Yin, Jingwei Yu, Ge Harbin Engn Univ Acoust Sci & Technol Lab Harbin 150001 Heilongjiang Peoples R China Harbin Engn Univ Coll Underwater Acoust Engn Harbin 150001 Heilongjiang Peoples R China Harbin Engn Univ Key Lab Marine Informat Acquisit & Secur Harbin 150001 Heilongjiang Peoples R China

ISBN: (纸本)9781538616543

Recently an underwater acoustic communication (UWA) experiment with a mobile source was conducted in downward-refracting shallow water environment. During this experiment, the source moved towards and then away from the receiving array repeatedly, Doppler effect kept changing in this process due to the time-varying radial velocity between the source and receiving array. In this paper, a three-stage data processing method is proposed in order to effectively decode the experimental data with severe Doppler interference. In the first stage, fractional Fourier transform (FrFT) is used to estimate the delay-Doppler function of the underwater channel based on the linear chirp signal at the front of the received data sequence. Large Doppler effect are coarsely removed according to the Doppler estimation result by resampling and delay estimation is used to determine the number of channel taps. Then the resampled data are demodulated and downsampled to the baseband. In the second stage, data are divided into small blocks and block-based passive time reversal (PTR) is adopted to suppress the mutipath in a block by block manner. Fine Doppler is also compensated in each block by maximum likelihood estimation method. In the third stage, decision feedback equalizer (DFE) is used to remove the residual inter symbol interference (ISI) and Doppler effect. data proceesing results show that this proposed three-stage equalization method can realize effective trakcing and compensation for time-varying channels. The output signal-to-noise ratio (OSNR) after equalization is greatly improved and the bit error rate (BER) is significantly reduced.

关键词： underwater acoustic communication three-stage data processing fractional Fourier transform passive time reversal

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Feature-aided Multi-Target Tracking Method in Sea Clutter Using Scanning Radar data

Feature-aided Multi-Target Tracking Method in Sea Clutter Us...

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IEEE International conference on signal and Image processing (ICSIP)

作者： Yingpei Zhu Zhen Wang Yupei Yin Weidong Chen University of Science and Technology of China Hefei P.R.China

ISBN: (纸本)9781665446006

Maritime multi-target tracking (MTT) is an important application scenario of radar target tracking technology, but it still faces huge challenges such as the interference of sea clutter and the fluctuation of target echoes, which leading to the trajectory fragmentation. Additionally, due to radar scanning, targets are extended in azimuth and cannot be regarded as point targets. In this paper, we construct the feature vector by combining the radar echo data with the extension estimation of targets obtained by gamma Gaussian inverse Wishart-probability hypothesis density (GGIW-PHD) filter. Then, the echo features of targets are introduced into MHT framework and trajectory management module, aiming to reduce trajectory fragmentation and improve the integrity of target trajectory. Finally, the effectiveness of the proposed method is verified by measured data.

关键词： Target tracking Fluctuations Radar measurements Radar clutter Sea measurements Radar Radar tracking

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Research on Media Cognition Practical Projects Curriculum 9

Research on Media Cognition Practical Projects Curriculum

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9th IEEE International conference on Computer Science and Education (ICCSE)

作者： Yang Yi Ma Xiaohong Sun Jiasong Deng Beixing Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

ISBN: (纸本)9781479929511

With the development of digital signal processing, the field of media cognition has more attention which is the necessary method to achieve human-computer interaction technology. The electronic media is a new human civilization carrier which will give birth to new culture and arts. Media cognition projects practice is set up to accomplish the target of cultivating talented person. This paper shows some new practical projects curriculum on media cognition. Students complete a series of small independent media cognition practical projects curriculum to fully stimulate students' interest in the related research areas. High-level talents will be trained by these practical projects. Analysis shows that the media cognition practical projects curriculum improved the ability to acquire the relevant knowledge and in-depth investigation of project programming.

关键词： Media cognition Practical projects curriculum Kinect Hardware data acquisition and analysis Pattern Recognition

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Multiple Target Vital Sign Detection Using Ultra-Wideband Radar

Multiple Target Vital Sign Detection Using Ultra-Wideband Ra...

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International conference on signal and Information processing (IConSIP)

作者： Asmita Wankhade Abhijeet V. Nandedkar S. M. Rathod Yashodip Amritkar Suryakant Rathod Ajay Sharma Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded Maharashtra India Defence R&D- KCTI Bharat Forge Limited Pune Maharashtra INDIA

ISBN: (纸本)9781728168869

Detection of living beings through wall or under the rubble/debris is difficult in Radar due to low signal to noise ratio (SNR). To improve SNR and extract vital signs from Radar echo signal advanced signal processing techniques are required. The existing methods focus on detection of vital sign for single target only. This paper proposes an improvised method to detect multiple vital signs by determining the number of targets and their breathing frequency behind the wall using fast Fourier transform (FFT). Additionally an alternative technique using deep learning has been proposed for faster pre-processing and classification of number of targets. The proposed convolutional neural network (CNN) model is compared with other machine learning classifiers. It is found that if we used CNN as a feature extractor layer and Random Forest (RF) classifier it works the best with 94.38% accuracy (for two targets) and 73.33% accuracy (for three targets) without any pre-processing on Radar data. This method reduces the detection time needed as compared to the conventional algorithms available in literature

关键词： Radar detection signal processing algorithms Radar Feature extraction Convolutional neural networks data mining Standards

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