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Radar signal Modulation Recognition based on 1-D CNN

Radar Signal Modulation Recognition based on 1-D CNN

引用

IEEE advanced Information Management,Communicates,Electronic and Automation Control conference (IMCEC)

作者： Dongming Wu Fangzheng Liu Shilong Wu Zhenzhong Han National University of Defense Technology Hefei China

ISBN: (纸本)9781665479691

In order to solve the problems of low recognition accuracy and high computation complexity of radar signal processing under low signal-to-noise ratio (SNR), this paper studies a neural network based on 1-D convolution for radar intra-pulse modulation recognition. First, we generate seven different types of radar continuous FM signals and phase coded signals (LFM, NLFM, Frank, P1, P2, P3, P4). Then, the three-dimensional convolutional network suitable for image processing is improved into a one-dimensional convolutional network which will process the generated radar signal in an end-to-end approach. The simulation results show that the recognition algorithm using one-dimensional (1-D) MobileNetV2 network can effectively extract the essential characteristics of radar signal under the condition of low SNR, avoid the huge calculation caused by using time-frequency method, and achieve over 85% recognition accuracy at −6dB.

关键词： Time-frequency analysis Convolution signal processing algorithms Radar Radar imaging Feature extraction Radar signal processing

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Development and Application of Transformer State Perception Terminals Based on Artificial Intelligence and Edge Computing

Development and Application of Transformer State Perception ...

引用

Energy Engineering and Power Systems (EEPS), International conference on

作者： Xintong Wang Xin Chen Xuexing Zhang Zhendong Tang State grid Jibei Electric Power Co. Ltd. Tangshan power supply company Tangshan China

ISBN: (数字)9798350366914

ISBN: (纸本)9798350366921

The arrival of the global digital and intelligent revolution has profoundly changed the fundamental structure and operational basis of various industries, making the energy transition and digital development of power systems an inevitable trend. However, the rapid development of sensor and communication technologies has increasingly highlighted the bottleneck in data processing capabilities. With the widespread installation of sensors, power equipment continuously generates massive amounts of state monitoring data, and traditional data analysis algorithms are unable to cope with the growing backlog of data. To address this challenge, this paper explores the feasibility of integrating advanced artificial intelligence technologies on the edge computing platform for efficient real-time processing and analysis at the data source. The paper focuses on the development and application of edge computing terminals for current transformer state perception. By analyzing the problems and challenges in the current operation and control of current transformers, an edge computing service framework suitable for current transformer state detection is constructed based on edge computing. In conjunction with actual application needs, this paper proposes effective edge computing implementation solutions. The research results show that this solution significantly improves data processing efficiency and accuracy, playing an important role in promoting the intelligent monitoring and maintenance of current transformers.

关键词： Current transformers Soft sensors Computational modeling Real-time systems Power systems Convolutional neural networks Artificial intelligence signal analysis Monitoring Edge computing

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FineQ: Software-Hardware Co-Design for Low-Bit Fine-Grained Mixed-Precision Quantization of LLMs

FineQ: Software-Hardware Co-Design for Low-Bit Fine-Grained ...

引用

Design, Automation and Test in Europe conference and Exhibition

作者： Xilong Xie Liang Wang Limin Xiao Meng Han Lin Sun Shuai Zheng Xiangrong Xu School of Computer Science and Engineering Beihang University Beijing China Jiangsu Shuguang Optoelectric Co. Ltd

ISBN: (数字)9783982674100

ISBN: (纸本)9798331534646

Large language models (LLMs) have significantly advanced the natural language processing paradigm but impose substantial demands on memory and computational resources. Quantization is one of the most effective ways to reduce memory consumption of LLMs. However, advanced single-precision quantization methods experience significant accuracy degradation when quantizing to ultra-low bits. Existing mixed-precision quantization methods are quantized by groups with coarse granularity. Employing high precision for group data leads to substantial memory overhead, whereas low precision severely impacts model accuracy. To address this issue, we propose FineQ, software-hardware co-design for low-bit fine-grained mixed-precision quantization of LLMs. First, FineQ partitions the weights into finer-grained clusters and considers the distribution of outliers within these clusters, thus achieving a balance between model accuracy and memory overhead. Then, we propose an outlier protection mechanism within clusters that uses 3 bits to represent outliers and introduce an encoding scheme for index and data concatenation to enable aligned memory access. Finally, we introduce an accelerator utilizing temporal coding that effectively supports the quantization algorithm while simplifying the multipliers in the systolic array. FineQ achieves higher model accuracy compared to the SOTA mixed-precision quantization algorithm at a close average bit-width. Meanwhile, the accelerator achieves up to 1.79x energy efficiency and reduces the area of the systolic array by 61.2%.

关键词： Quantization (signal) Accuracy Large language models Memory management Clustering algorithms Systolic arrays Encoding Energy efficiency Natural language processing Protection

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Stepwise DOA Estimation for Coherent and Uncorrelated Mixed signals on Coprime Array

Stepwise DOA Estimation for Coherent and Uncorrelated Mixed ...

引用

IEEE advanced Information Management,Communicates,Electronic and Automation Control conference (IMCEC)

作者： Heng Jiang Lichun Li Hailong Zhang Hongyi Pan Xue Li College of Information System Engineering Information Engineering University Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665479691

The coprime array constructs virtual array to obtain higher degrees of freedom (DOF), but the premise of doing so is that the signals are independent of each other. Once there are coherent signals, the signal model of virtual array is destroyed and the method fails. To solve these problems, we propose the stepwise estimation of the Direction of Arrival (DOA) for a mixture of coherent and uncorrelated signals. Firstly, the symmetry of the two coprime subarrays is used to eliminate the uncorrelated signals, and combined with the properties of prime numbers, the coherent source DOA is jointly estimated. The obtained coherent source DOA was combined with the optimization algorithm to remove the coherent signal in the mixed signal. Finally, the virtual domain signal processing method was used to estimate the independent source DOA. This method can effectively reduce the influence of coherent signals on the accuracy of DOA estimation without loss of degrees of freedom. In this paper, the feasibility of the proposed method is proved by theoretical derivation, and the effectiveness of the method is also verified by experimental simulations.

关键词： Direction-of-arrival estimation Automation Simulation Estimation signal processing algorithms Interference signal processing

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UVM-Based Verification of OFDM Baseband processing System

UVM-Based Verification of OFDM Baseband Processing System

引用

International conference on Communication Engineering and Technology (ICCET)

作者： Chengcheng Zhao Jianning Yang Jiansong Tian Xin Deng Yuanhui Cai Mei Yang School of Information and Electronics Beijing Institute of Technology Beijing China School of Arts and Sciences Beijing Institute Of Fashion Technology Beijing China

With the development of very large scale integrated circuit (VLSI), verification becomes an indispensable step to ensure the normal operation of digital circuits. In the face of increasing complex large-scale digital design, universal verification methodology (UVM) has become the mainstream verification method due to its scalability, standardization, portability and other characteristics. Orthogonal frequency division multiplexing (OFDM) is an advanced multi-carrier transmission technology, which is widely used in the field of wireless communication. This paper presents a verification framework of OFDM baseband processing system based on UVM. UVM generates random excitation and passes it to our design, and automatically collects the results and compares them with the reference model to achieve sufficient verification of the system. Simulation results show the final functional coverage reaches 100%, demonstrating the validity of our verification framework.

关键词： Wireless communication Baseband OFDM Simulation Scalability signal processing algorithms Standardization

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International Youth conference on Electronics, Telecommunications, and Information Technologies, YETI 2021

International Youth Conference on Electronics, Telecommunica...

引用

International Youth conference on Electronics, Telecommunications, and Information Technologies, YETI 2021

ISBN: (纸本)9783030811181

The proceedings contain 64 papers. The special focus in this conference is on Electronics, Telecommunications, and Information Technologies. The topics include: Application of Deep Learning Techniques for Detection of COVID-19 Using Lung CT Scans: Model Development and Validation;preface;synthesis and Analysis of Avionics Functions Digital Twins Using Machine Learning Classification algorithms;algorithm for the Joint Analysis of Beat-To-Beat Arterial Pressure and Stroke Volume for Studying Systemic Vasoconstrictor and Vasodilator Responses;development of Simple Model of the Arterial Baroreflex;Analysis of Classification Methods for Wi-Fi signals Based on the Use of Channel State Information Spatial Features and CNN;application of Top-Down Deconvolution Tools to Bottom-Up Mass Spectrometry Data: Advantages and Limitations;algorithm for Fetal Activity Passive Monitoring;lossless Genome Data Compression Using V-Gram;The Method of Generating Random OQPSK signal Packets Based on Optimal FTN Pulses with Reduced PAPR and Frequency Band;iterative Algorithm with Feedback for Coherent Detection of Non-orthogonal Spectrally Efficient Multi-frequency signals;development of a Universal System for Three-Dimensional Data Visualization;Extracting Human Brain signals from the EEG Records Using LabVIEW and advanced signal processing;on the Application of a Fully Connected Neural Network for Multifrequency signals Demodulation;identification of Mortality Predictors for Elderly Patients with Airway Cancer;FPGA Implementation of Outer Decoders for Sequential Decoder of Polar Codes;integrated Digital Voltage Regulator with Phase-Frequency Control for Wireless Passive Microdevices;Aerosol Transport Modeling for Evaporator of CVD Reactor;Numerical Simulation of CVD Reactor for Oxide Semiconductor Layer Deposition;design of GaAs Flip-Flop Using Depletion-Mode-Only Transistors;comparative Study of Ion-Induced Damage Formation in GaN and beta-Ga2O3.

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Optimization of supply chain in iron and steel industry based on pre flow advancing network flow algorithm and computer simulation

Optimization of supply chain in iron and steel industry base...

引用

signal processing, Communications and Engineering Management conference (ISPCEM), International

作者： Runtao Zhang Zhichao Zhang Green and Intelligent Building Industrial Internet Joint Laboratory Institute of Advanced Information Technology Peking University Hangzhou China

Under the relatively mature background of the iron and steel industry, the focus of industrial optimization is focused on the optimization of the logistics supply chain. In this paper, a large amount of data is extracted from the preventive maintenance inspection of the iron and steel industry supply chain, and a model to improve the transportation efficiency and test the maximum production and transportation capacity is constructed. Using the pre-flow propulsion network flow algorithm to solve the problem at high speed, it aims to quickly solve the model target value under the dynamic and diverse conditions. Taking the simulated industry situation in Zhejiang as an example, the network transport flow model and method proposed in this paper are verified to solve the problem of supply chain optimization and calculation in the iron and steel industry.

关键词： Heuristic algorithms Supply chains signal processing algorithms Steel industry Transportation Propulsion Iron

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Machine Learning-based Spectrum Sensing Techniques for Optimized Spectrum Utilization in Cognitive Radio Networks

Machine Learning-based Spectrum Sensing Techniques for Optim...

引用

Advancement in Technology (ICONAT), International conference for

作者： Pavan Chaudhary Rajesh Gupta H Malathi Maharishi University of Information Technology Uttar Pradesh India Department of Management Sanskriti University Mathura Uttar Pradesh India Department of Biotechnology and Genetics School of Sciences JAIN (Deemed to be University) Bangalore Karnataka India

ISBN: (数字)9798350354171

ISBN: (纸本)9798350354188

the usage of cognitive radios has enabled dynamic spectrum to get the right of entry to spectrum-congested regions. It has revolutionized how spectrum is allotted with the aid of turning the conventional static spectrum allocation into a dynamic and opportunistic method. Gadget studying-based totally spectrum sensing techniques have been advanced to permit optimized spectrum usage with better accuracy in cognitive radio networks. Those strategies use machine learning algorithms to learn the behaviors of spectrum assets and adaptively replace sensing strategies by intelligently deciding on the maximum suitable spectrum. This manner permits faster and more correct sensing in comparison to traditional spectrum sensing strategies. Furthermore, various fashions were proposed for specific spectrum sensing functionalities together with signal category, spectrum prediction, and function extraction. Those fashions are employed that allow you to maximize the spectrum assets utilization in cognitive radio networks. Furthermore, diverse processes have been proposed with the purpose of improving the overall performance of spectrum sensing techniques. Those consist of the usage of deep mastering fashions, exploiting heterogeneous facts sources, and using ensemble getting-to-know strategies. These approaches remember the complexity of the environment and permit extra correct and reliable choices. To conclude, device learning-based spectrum sensing techniques preserve a fantastic capacity for optimized spectrum utilization in cognitive radio networks. Consequently, they constitute a vital step forward closer to the improvement of green and reliable verbal exchange structures.

关键词： Performance evaluation Accuracy Noise signal processing algorithms Turning Sensors Complexity theory Cognitive radio Reliability Resource management

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Research on imaging coordinate system of time-domain algorithm in BI-SAR system

Research on imaging coordinate system of time-domain algorit...

引用

IET International Radar conference (IRC 2023)

作者： Peiyun An Tianyi Cai Yachao Li Qin Zhong Xuanqi Wang Yuzhou Liu National Key Laboratory of Radar Signal Processing Xidian University Xi'an People's Republic of China Beijing Institute of Remote-Sensing Equipment Beijing People's Republic of China Academy of Advanced Interdisciplinary Research Xidian University Xi'an People's Republic of China

ISBN: (数字)9781837240982

The time-domain imaging algorithm can meet the imaging requirements of bistatic synthetic aperture radar(Bi-SAR) system with flexible and complex configurations, and establishing the imaging coordinate system is the key step especially for Fast Time-Domain algorithms. In this paper, to simplify the establishment of imaging coordinate system, the orthogonal elliptical mapping polar (OEMP) coordinate system is proposed and used in the frame of the fast factorized back projection(FFBP) algorithm. Compared to the orthogonal elliptical polar(OEP) coordinate system, the proposed coordinate system has simpler coordinate solving, and can also reduce the computational burden of the FFBP algorithms. The applicability and performance of the OEMP-based FFBP algorithm is verified through simulation experiments.

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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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