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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101-110 订阅

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Hierarchical data-driven Scheduling-Control Framework for Energy-efficient Industrial Flexible Production 24

Hierarchical Data-driven Scheduling-Control Framework for En...

引用

2nd international conference on Frontiers of Intelligent Manufacturing and Automation, CFIMA 2024

作者： Jiang, Yuliang Zhu, Shanying Guan, Xinping Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (纸本)9798400710681

This paper proposes a hierarchical data-driven scheduling-control framework for a multi-machine/mode production system to operate in an energy-efficient manner. At the scheduling layer, the scheduling problem incorporating process dynamics is formulated into a quadratic programming to arrange candidate processing machines/modes and corresponding production objectives. Based on the dynamic linearization model, scheduling results are executed by model-free adaptive control at the control layer. The real-time process output is feedback to the scheduling layer for the next decision-making. The practicality of the proposed framework is validated in a thread-tapping process featuring four distinct operational modes. On average, operating in a single mode maintains output accuracy while saving 14.2% on energy. The multi-mode operation further optimizes energy usage through its capability for dynamic mode switching. © 2024 Copyright held by the owner/author(s).

关键词： Quadratic programming

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A Terrain data-Assisted Tracking Method for Rolling Rock 2

A Terrain Data-Assisted Tracking Method for Rolling Rock

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

作者： Chang, Ningyuan Chen, Youwang Lin, Ruiqi Tian, Weiming Deng, Yunkai Beijing Institute of Technology Radar Technology Research Institute Beijing China Beijing Institute of Technology School of Information and Electronic Beijing China Beijing Institute of Technology Advanced Technology Research Institute Jinan China

ISBN: (纸本)9798331515669

The rolling rock's trajectory is variable and complex, which could easily cause false associations, and affect tracking accuracy. To address this issue, a rolling rock tracking method based on terrain data assistance is proposed. Firstly, three-dimensional (3D) terrain data is utilized to predict the rolling rock's motion direction and project it onto a two-dimensional(2D) radar coordinate system. Then, based on the deviation between the associated measurements and the predicted direction, false association are rejected, and the state and covariance matrix are corrected using the Extended Kalman Filter (EKF). Finally, the correction of rolling rock trajectory is achieved, enhancing tracking performance. Experimental data is used to validate the effectiveness of this method. © 2024 IEEE.

关键词： Extended Kalman filters

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EMG signal processing for Disease Classification using Machine Learning 2

EMG Signal Processing for Disease Classification using Machi...

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2nd DMIHER international conference on Artificial Intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Awachat, Harshita S. Rewatkar, Rajendra Reddy, K.T.V. Datta Meghe Institute of Higher Education and Research Wardha India

ISBN: (纸本)9798331528713

Electromyography (EMG) plays a crucial role in the medical sector for assessing muscular health and diagnosing related ailments. With a growing global demand for EMG equipment and its surpassing significance over other diagnostic tools, EMG has become instrumental in addressing muscle disorders and designing prosthetic limbs. EMG captures electrical impulses generated during muscle activities, finding applications in medical, biological, and human-computer interface realms. Recent studies have delved deep into refining EMG signal processing through various machine learning algorithms, such as neural networks and support vector machines. This paper comprehensively reviews methodologies that include supervised learning, unsupervised learning, data preprocessing, feature extraction, classification algorithms such as real-time classification, and performance evaluation. The synthesis of cutting-edge techniques from interdisciplinary sectors promises a brighter future for EMG-based applications, particularly in assistive technologies. The writer has made effort for understanding better categorization of EMG signals for more significant research. © 2024 IEEE.

关键词： Support vector machines

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PS Point Selection Based on Phase Stability of Time Series Phase Unwrapping 2

PS Point Selection Based on Phase Stability of Time Series P...

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

作者： Yang, Yiqi Li, Zhenfang Cao, Yuting Xidian University School of Electronic Engineering Xi'an China Xidian University National Key Laboratory of Radar Signal Processing Xi'an China

ISBN: (纸本)9798331515669

In Time Series SAR interferometry (TS-InSAR) analysis, the screening results of permanent scatterers (PS points) affect the accuracy and efficiency of phase unwrapping of TS-InSAR. In the case of atmospheric effect and random noise, the traditional PS point screening method will lead to incomplete noise removal and loss of key deformation information points. To solve this problem, a phase stability PS point screening method based on the traditional method is proposed in this paper. By analyzing the influence of the noise residual phase on the interference vector distribution, this method proposes a formula for calculating the phase coherence coefficient of a long time series midpoint. By setting a reasonable threshold to screen the phase coherence of global points, PS points that are relatively stable in amplitude and phase can be obtained, and the efficiency of subsequent phase unwinding and the precision of processing results can be improved. © 2024 IEEE.

关键词： Phase noise

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Wall Compensation for Through-Wall Radar Imaging Based on LiDAR Point Cloud data 2

Wall Compensation for Through-Wall Radar Imaging Based on Li...

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

作者： Hu, Yang Zeng, Xiaolu Yin, Zixiang Yang, Yifei Zhou, Jiali Yang, Xiaopeng Beijing Institute of Technology School of Information and Electronics Beijing China Yangtze Delta Region Academy Beijing Institute of Technology Jiaxing China

ISBN: (纸本)9798331515669

With the advancement of through-wall radar technology, its applications have become increasingly important in many applications such as security monitoring, disaster rescue, etc. To mitigate the impact of irregularities such as doors, windows, pillars, and protrusions on non-uniform building walls during through-wall imaging, this paper proposes a wall compensation method based on LiDAR(Light Detection And Ranging) point cloud data. By integrating measurements from both LiDAR and through-wall radar, and employing the ICP(Iterative Closest Point) algorithm, point cloud preprocessing and contour fitting techniques, accurate wall contour information is obtained, enabling effective wall compensation. Experimental results demonstrate that the accuracy of building interior layout reconstruction is significantly improved by compensating the impact of the external wall extracted by LiDAR. © 2024 IEEE.

关键词： Optical radar

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Research on Adaptive signal Optimization Algorithm of Intelligent Decision Support Enterprise Based on Deep Learning 2

Research on Adaptive Signal Optimization Algorithm of Intell...

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2nd IEEE international conference on Sensors, Electronics and Computer Engineering, ICSECE 2024

作者： Yu, Junyu School of Management Shanghai University Shanghai China

ISBN: (纸本)9798350373646

In order to solve the problems such as low efficiency of cloud manufacturing resource allocation and unreasonable selection of manufacturing services, this project intends to study the resource-oriented cloud manufacturing resource allocation strategy based on user demand. By introducing the methods of data warehouse, online analysis and processing, and data mining, the functional model of ERP data analysis is established. The dual-track mechanism of case base and model base is applied to the process design of model intelligent decision support system (IDSS) and the corresponding algorithm is proposed. A multi-index optimization modeling method for cloud manufacturing based on time-expense-quality-of-service and customer satisfaction was constructed. In this project, Chebyshev filter is combined with second-order vibration to solve the problem of early convergence of particle swarm. The variation factor is added to the subjective weight to reflect the contrast strength of the target data. The numerical simulation shows that the new algorithm has a wide range of solutions and good convergence performance, and also proves the correctness of the proposed theory and decision method. © 2024 IEEE.

关键词： Chebyshev filters

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Exploring Sub-Nyquist Sampling for Fine Image Reconstruction 2

Exploring Sub-Nyquist Sampling for Fine Image Reconstruction

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2nd international conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2024

作者： Nithya, M. Satheeshkumar, S. Dakshana, M. Gunalan, K. Anandan, P. Saveetha, R. Bannari Amman Institute of Technology Department of Computer Technology Tamilnadu India Bannari Amman Institute of Technology Department of Artificial intelligence and data science Tamilnadu India Sathyabama Institute of Science and Technology Department of Physics Tamilnadu India

ISBN: (纸本)9798350368413

Compared to traditional methods, compressive sensing, a signal processing technique, allows for the effective acquisition and reconstruction of signals. A rate that is less than twice the highest frequency component of a signal is known as subNyquist sampling, allows for the digitization of wideband frequency-domain sparse signals without compromising reconstruction quality when employing compression sensing (CS). According to the CS framework, samples taken at sub- Nyquist sampling rates can be used to reconstruct signals with sparse representations in a known basis. Because of its inherent qualities, the Fourier domain is frequently used in compressive sensing applications. Use of a small number of Fourier transform coefficients in sparse signal recovery applications has led to successful resolutions of large-scale data recovery issues, including image recovery. During the measurement phase, input is systematically measured in blocks to obtain the necessary data, while in the recovery phase, all measurements from a single image are simultaneously utilized to reconstruct the complete image. © 2024 IEEE.

关键词： Compressed sensing

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Enhanced SVD Denoising Method Based on Hankel Matrix Decomposition for Seismic data 2

Enhanced SVD Denoising Method Based on Hankel Matrix Decompo...

引用

2nd IEEE international conference on Image processing and Computer Applications, ICIPCA 2024

作者： Dai, Honglin Tang, Yucheng Han, Xiangyu Xiong, Weiming China University of Petroleum-Beijing at Karamay Faculty of Business Administration Karamay City China Petroleum Institute China University of Petroleum-Beijing at Karamay Karamay City China

ISBN: (纸本)9798350360240

This study introduces an improved SVD denoising method based on the decomposition of the Hankel matrix. This method denoises by analyzing the singular value spectrum of the Hankel matrix, where larger singular values typically represent components with higher coherence in the data, and smaller singular values correspond to less coherent parts. By selecting different rank reduction parameters based on the characteristics of the processed data, this method achieves noise reduction and enhances SNR. Subsequently, a two-dimensional seismic data model is constructed to validate this algorithm. The key to this algorithm is determining the truncation position of the singular value matrix (rank reduction parameter), and the optimal rank reduction parameter is efficiently found using the energy ratio. Practical case studies have shown a significant improvement in the SNR of incoherent data, effectively suppressing random noise and improving the denoising effect for non-horizontal coherent axes. Overall, the Hankel matrix construction method effectively suppresses random noise while maintaining high fidelity of the signal data. © 2024 IEEE.

关键词： Singular value decomposition

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Phase unwrapping in DOA estimation via on the least squares of the nearest projection point 2

Phase unwrapping in DOA estimation via on the least squares ...

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

作者： Wang, Xiaoyan He, Huiqun Xie, Jian Sun, Yandong Wang, Ling Liu, Yanyang Northwestern Polytechnical University School of Electronics and Information Xi'an710072 China Shanghai Academy of Spaceflight Technology Shanghai201109 China Shanghai Institute of Satellite Engineering Shanghai201109 China

ISBN: (纸本)9798331515669

The phase interferometer offers a number of advantages, including a simple structure, high direction-finding performance and low computational complexity. As a result, it has become a popular technique for Passive Direction Finding. However, the phase interferometer is significantly affected by phase measurement error, which can easily lead to phase ambiguity when the minimum element spacing exceeds half a wavelength. For this, we propose an enhanced least squares nearest projection point (LS-NPP) phase unwrapping algorithm. By fitting multiple snapshots of phase-difference points using the least squares method, and then utilizing the wrapped phase-difference pattern (WPDP) to identify the nearest phase projection point to the fitted phase point, the ambiguity number is obtained, thereby achieving phase unwrapping. Simulation results demonstrate that the proposed algorithm exhibits a higher probability of correct phase unwrapping under low signal-to-noise ratio (SNR) conditions. © 2024 IEEE.

关键词： signal to noise ratio

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Algorithm Analysis and Application of Digital signal processing Technology 2

Algorithm Analysis and Application of Digital Signal Process...

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2nd international conference for Innovation in Technology, INOCON 2023

作者： Yuanmin, Wang Li, Zhang Leshan Vocational and Technical College Sichuan Leshan614000 China

ISBN: (纸本)9798350320923

Digital signal processing is a rapidly developing field of science and technology. In the 1960s and 1970s, it experienced the development stages of digital filtering theory, signal Fourier transform, convolution and fast correlation calculation. Subsequently, the rapid development of computer technology and microelectronics technology promoted the development of digital signal processing technology and pushed it to a climax. Algorithm analysis is the study of algorithms. An algorithm is a set of rules that explain how to solve computer programming problems. The most common algorithm is the search and sort algorithm, which tells you how to find what you need in a large group of items. It is also used to search files or databases, group data, or find patterns in a dataset. The method adopted in this paper is to use FPGA to complete the signal preprocessing and STFT algorithm implementation. The necessary parameters and data results obtained from FPGA processing are transferred to DSP through the interface in a handshake manner, and the DSP completes the subsequent modulation analysis and parameter estimation. This method is much more efficient and reliable than using DSP alone to complete all processes in the past, and greatly shortens the cycle of intra pulse analysis. © 2023 IEEE.

关键词： Digital signal processing

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