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检索条件"任意字段=2nd International Conference on Signal and Data Processing, ICSDP 2022"

共 3161 条记录，以下是131-140 订阅

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Calibration-Based 2-D DOA Estimation Exploiting 2qth-Order Cumulants for Polarimetric Arrays 2

Calibration-Based 2-D DOA Estimation Exploiting 2qth-Order C...

引用

2nd IEEE international conference on signal, Information and data processing, ICSIDP 2024

作者： Yang, Jiaming Fu, Zheng Zhang, Zexiang Zhou, Aoxuan Shen, Qing Beijing Institute of Technology School of Information and Electronics Beijing China

ISBN: (纸本)9798331515669

In practical engineering, there exist various types of array errors, causing significant degradation in direction finding performance. As a result, array calibration plays a crucial role in practical array signal processing. In this paper, a calibration-based two-dimensional (2-D) direction of arrival (DOA) estimation method based on 2qth-order cumulants is proposed, which can be applied to arbitrary polarimetric arrays with unknown array errors. All the errors are modeled into a non-parametric angle-dependent error matrix. The array output across 2-D potential angle grids are obtained by placing two calibration sources with arbitrary but different polarimetric parameters. Subsequently, an array calibration matrix is generated from the calibration process. The equivalence of the matrix pencils calculated by the calibration matrix and the non-ideal error-corrupted matrix is proven, forming a low-complexity calibrated polarization diversity 2q-MUSIC (CPD-2q-MUSIC) method without reconstructing the error matrix incorporating all array errors. Simulation results demonstrate the effectiveness of the proposed method. © 2024 IEEE.

关键词： Direction of arrival

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Comparison of Pansharpening Algorithms: Developing a data-Driven Evaluation Framework 2

Comparison of Pansharpening Algorithms: Developing a Data-Dr...

引用

2nd IEEE international conference on signal, Information and data processing, ICSIDP 2024

作者： Liu, Yu Tong, Qingwei Zhao, Zhipeng Southwest Forestry University School of Big Data and Intelligent Engineering Kunming China

ISBN: (纸本)9798331515669

Convolutional neural network (CNN)-based methods are increasingly crucial in image processing and computer vision. In remote sensing image pansharpening, CNNs have shown excellent fusion performance, attracting significant research interest. However, challenges remain, such as the lack of detailed pansharpening dataset simulations, standardized training-testing datasets, and simple, unified coding frameworks. Additionally, there is insufficient evaluation of recent deep learning pansharpening methods and evaluation of algorithms from the perspective of different subsequent applications, limiting comprehensive evaluation. This study constructs a comprehensive evaluation system for datasets, fusion algorithms, and evaluation methods. By statistically analyzing results, improve the accuracy and richness of algorithm evaluations, enabling more effective and objective method comparisons. Used WorldView-2 satellite imagery for visual assessments, supervised and unsupervised quantitative evaluations on 100 images, and land cover classification accuracy experiments. Traditional methods like BDSD and PRACS showed strong fusion results and land cover classification accuracy, deep learning methods generally outperformed traditional ones. This research provides detailed images and data resources for pansharpening, offering valuable references for future studies in this field. © 2024 IEEE.

关键词： deep learning Pansharpening quality assessment (key words) remote

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Software radio-based hybrid radar data acquisition and real-time transmission system 2

Software radio-based hybrid radar data acquisition and real-...

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2nd IEEE international conference on signal, Information and data processing, ICSIDP 2024

作者： Luo, Linsheng Liu, Xiao-Tian Wang, Hai-Tao Xia, Tian Wang, Li Chang, Kai Guilin University of Electronic Technology School of Information and Communication Guilin541004 China Guizhou Space Appliance Co. Ltd. Guizhou Guiyang550009 China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515669

In this paper, a hybrid radar data acquisition and real-time transmission system based on software radio is proposed to solve the problems of poor flexibility and versatility of traditional single-functionality radar systems in multifunctional applications as well as poor real-time performance of the system transmission data. The system includes a host computer and a software radio platform. The host computer mainly completes the setting of control parameters and the control of the whole system, this paper utilizes the HJX-ADRV9009-X2 software radio platform to realize the radar data acquisition and real-time transmission under the three working modes of active detection, passive reconnaissance and active detection + passive reconnaissance. After testing, the system data transmission rate can reach 9.3Gbps. the system is more versatile and real-time, and can realize the function of multi-purpose in practical use. © 2024 IEEE.

关键词： Software testing

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Comparison Between Yoga And Non Yoga Eeg signal Analysis 2

Comparison Between Yoga And Non Yoga Eeg Signal Analysis

引用

2nd IEEE international conference on Networking and Communications, ICNWC 2024

作者： Rajalakshmi, A. Sridhar, S.S. SRM Institute of Science and Technology Department of Computing Technology Chennai India

ISBN: (纸本)9798350365269

Electroencephalography is a non-invasive technique used to monitor brain activity and make a variety of neurological problems diagnoses. The electrical activity of the brain is measured using an EEG instrument, which converts chemical variations in the brain into voltage. With either the intracranial EEG method or the Scalp EEG approach, several electrodes are implanted at the right location on the brain to measure EEG signals. Analysis of electroencephalograms, or EEGs, has grown to be crucial for identifying many human disorders. The most crucial and straightforward step in processing EEG readings is using temporal frequency analysis to make a potential diagnosis. EEG signals are the important data for any type of analysis of brain activity. In this study, we first analysis the EEG signal characteristics that have been used in the literature for a variety of activities, then we concentrate on looking at EEG feature applications, and finally we talk about the potential and unresolved issues with EEG feature extraction. Everyone should assess the wide variety of EEG signal properties and their effects on BCI interfaces in order to improve the accuracy of different brain activity detection in the future. © 2024 IEEE.

关键词： Electroencephalography

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GraphRTL: an Agile Design Framework of RTL Code from data Flow Graphs

GraphRTL: an Agile Design Framework of RTL Code from Data Fl...

引用

2nd international Symposium of Electronics Design Automation (ISEDA)

作者： Qiao, Yuheng Xie, Cai Ou, Zhaoting Lei, Peizhi Tian, Yan Chen, Jienan Univ Elect Sci & Technol China Chengdu 611731 Peoples R China

ISBN: (纸本)9798350352047;9798350352030

As the increasing demand for large and complex signal processing requirements, the efficient and fast design of signal processing circuits becomes an important issues. Agile design offers a new approach for rapid hardware design cycles. While this approach is a standard for software design, how to adapt it to hardware design properly remains an open question. In our work, we propose a framework for agile software and hardware co-design named GraphRTL. The tool addresses the challenge of designing hardware for Digital signal processing (DSP). Instead of direct coding and debugging iteration, we employ data flow graphs (DFG) and control flow graphs (CFG) to automatically generate RTL code. The input to GraphRTL is the flow graph of the designed circuit. Subsequently, the tool checks the graphs, reconstructs it, and then translates it into a configuration file for the compiler. Finally, the compiler autonomously generates the corresponding software to hardware code and RTL code. Compared to the traditional design route, GraphRTL enhances design efficiency and broadens the design space. In our experiments, we achieved up to an 70% reduction in design time while maintaining a 5 to 10% reduction in hardware overhead for the designed circuits.

关键词： data Flow Graph Control Flow Graph Agile Design Compilers Digital signal processing RTL

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Adaptive Control of Starting Point Based on System data Degradation SCR 2

Adaptive Control of Starting Point Based on System Data Degr...

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2nd international conference on Computer Vision and Intelligent Technology

作者： Wang, Jing Wen, Yudi Zhang, Ying China Acad Launch Vehicle Equipment Integrated Logist Support Ctr Projects Execut Off Beijing Peoples R China Beijing Aerosp Automat Control Inst Beijing Peoples R China Peking Univ Beijing Aerosp Automat Control Inst Natl Key Lab Sci & Technol Aerosp Intelligent Beijing Peoples R China

ISBN: (纸本)9798331540050;9798331540043

In this paper, the prediction starting point detection algorithm based on the real-time change trend of the state is used to divide and control the health status of the system data, and the adaptive control of the starting point threshold of life decay is carried out by analyzing the change trend of the SCR (State Change Rate) of the system data degradation process, so as to improve the accuracy of the prediction starting point detection. The time-domain and frequency-domain features of the processed signal are extracted, and the evaluation index is constructed through the monotonicity and predictiveness of the features, and the suitable features are selected as the basis for the remaining life prediction of the system data. High-dimensional feature processing and screening of system data. In this paper, through a large number of simulation experiments, the monotonicity law of system data features and the trend law of system data characteristics are obtained. The validity of weighting the monotonicity and trend of the system data features is verified, and the weight of monotonicity is 0.6 and the weight of trend is 0.4 in the verification system, and the calculation results of the evaluation index of each feature of the system data are obtained. It is concluded that the peak, variance, root square amplitude, root mean square value, kurtosis value and peak factor are used as inputs for the remaining life prediction for the degradation of the system data.

关键词： adaptive control starting point System data degradation SCR

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Supervised machine learning approaches for medical data classification 2

Supervised machine learning approaches for medical data clas...

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2nd international conference on Artificial Intelligence and signal processing, AISP 2022

作者： Dalai, A.K. Jena, A.K. Ramana, B.V. Maneesha, B. Panda, Nibedan School of Computer Science and Engineering VITAP University India Department of Information Technology Aditya Institute of Technology and Management AP Tekkali532201 India Department of CSE Presidency University Yelahanka Bengaluru560064 India

ISBN: (纸本)9781665442909

Recently there is an emergent curiosity among researchers to apply machine learning algorithms over diversified real world complications to get simpler *** notion behind this briefing is to represent the basic machine learning algorithms and its applicability in current research. Broadly machine learning algorithms falls to the category of either supervised or unsupervised learning technique. In this paper we have discussed supervised machine learning techniques with its simplicity to apply over various problem areas and simultaneously the challenges for such algorithms. Furthermore SVM and Random Forest (RF) are utilised learn, categorise, and compare cancer, liver, diabetes, iris, and heart data in this study. For all considered data sets, the results of SVM and RF are compared. The results are properly analysed in order to develop better prediction learning techniques. © 2022 IEEE.

关键词： Support vector machines

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A Novel Sparse Frequency Radar Waveform Employing Multi-frequency Component processing 2

A Novel Sparse Frequency Radar Waveform Employing Multi-freq...

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2nd IEEE international conference on signal, Information and data processing, ICSIDP 2024

作者： Du, Xiaohe Zhou, Shenghua Bai, Jian Qin, Jingshu Li, Aihua Xidian University National Key Laboratory of Radar Signal Processing Xi'an China Beijing Institute of Remote Sensing Equipment Beijing China

ISBN: (纸本)9798331515669

Traditional radar systems typically use wideband signals but have limited anti-jamming capabilities. Sparse frequency waveforms offer a solution to narrowband interference issues. However, existing sparse frequency waveform design methods often handle the entire signal uniformly, resulting in fixed frequency notch positions and limited waveform flexibility. In this paper, we propose a new method for optimizing sparse frequency waveforms. While maintaining constant waveform pulse width and range resolution, we increase the degree of freedom by extending the length of phase coded signals. Pulse compression is applied to each frequency band component with the objective of minimizing sidelobes, using the minimax algorithm based on sequential quadratic programming (SQP) to obtain optimal phase coded waveforms. Simulation results demonstrate the method's capability to flexibly design sparse frequency waveforms and reduce pulse compression sidelobe levels. © 2024 IEEE.

关键词： Quadratic programming

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An optimized scheme of computer-generated hologram compression with convolutional neural networks and genetic algorithm 2

An optimized scheme of computer-generated hologram compressi...

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2nd international conference on Optical Communication and Optical Information processing, OCOIP 2024

作者： Yao, Yuxuan Yang, Guanglin Laboratory of Signal and Information Processing School of Electronics Peking University Beijing100871 China

ISBN: (数字)9781510688995

ISBN: (纸本)9781510688988

Holography is pivotal in various applications ranging from microscopy to data storage. However, the practical implementation of holography often necessitates compression, which inevitably degrades the quality of the reconstructed images. Addressing this challenge, a scheme of computer-generated hologram compression with convolutional neural networks optimized is proposed. In this scheme, our research investigates the potential of genetic algorithm, a class of evolutionary algorithms inspired by natural selection, to optimize the initial weights of the network. Experimental results show that the scheme is feasible. © 2025 SPIE.

关键词： Convolutional neural networks

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Multisource data Integration of Sentinel-1 and Sentinel-2 for Above Ground Biomass Inversion 2

Multisource Data Integration of Sentinel-1 and Sentinel-2 fo...

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2nd IEEE international conference on signal, Information and data processing, ICSIDP 2024

作者： Xing, Yaxuan Lin, Huiping Zhu, Jingwen Wang, Feng Xu, Feng Jiang, Wen School of Information Science and Technology Shanghai China Chinese Academy of Sciences Aerial Remote Sensing Center Aerospace Information Research Institute Beijing China

ISBN: (纸本)9798331515669

Remote sensing data provides several advantages for vegetation parameter inversion, including non-invasive measurement, high spatiotemporal resolution, and extensive coverage. However, as multisource remote sensing data continues to advance, challenges emerge in data fusion, particularly in ensuring consistency across various data sources and addressing physical differences among them. To address such challenges, this paper employs multisource re mote sensing data as inputs for Above Ground Biomass (AGB) inversion. As a scattering model, the Water Cloud Model (WCM) is widely adopted for vegetation parameter inversion due to its simplicity and ability to describe both vegetation and soil scattering mechanisms. In this study, Sentinel-1 data is utilized to extract backscatter coefficients and incidence angle information, while Sentinel-2 multispectral data is used to calculate soil moisture through the tasseled cap transformation. These variables are employed to calibrate the coefficients of the WCM, facilitating the bio mass inversion process. The approach effectively integrates multiple sources of remote sensing data, overcoming limitation of data saturation typically associated with single-source data, and achieving accurate biomass inversion across different polarization modes. © 2024 IEEE.

关键词： Abiotic

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