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Graph signal processing: Foundations and Emerging Directions [From the Guest Editors]

IEEE signal processing MAGAZINE 2020年第6期37卷 11-13页

作者： Marques, Antonio G. Kiyavash, Negar Moura, Jose M. F. van de Ville, Dimitri Willett, Rebecca King Juan Carlos Univ Dept Signal Theory & Commun Madrid Spain Ecole Polytech Fed Lausanne EPFL Coll Management Technol Business Analyt Lausanne Switzerland Georgia Inst Technol Georgia Tech Sch ECE H Milton Stewart Sch Ind & Syst Engn Atlanta GA USA Univ Illinois Chicago IL 60680 USA Carnegie Mellon Univ CMU Pittsburgh PA USA CMU CMU Portugal Program Pittsburgh PA USA Acad Sci Portugal Lisbon Portugal US Natl Acad Engn Washington DC USA Univ Geneva Bioengn EPFL Geneva Switzerland Univ Chicago Stat & Comp Sci Chicago IL 60637 USA Duke Univ Elect & Comp Engn Durham NC 27706 USA Univ Wisconsin Elect & Comp Engn Madison WI USA Univ Wisconsin Wisconsin Inst Discovery Madison WI USA

The articles in this special section focus on graph signal processing. Generically, the networks that sustain our societies can be understood as complex systems formed by multiple nodes, where global network behavior arises from local interactions between connected nodes. More succinctly, a network or a graph can be defined as a structure that encodes relationships between pairs of elements of a set. The simplicity of this definition drives the application of graphs and networks to a wide variety of disciplines, such as biology, medicine, psychology, sociology, economics, engineering, computer science, and so on.

关键词： Special issues and sections Graphic models signal processing algorithms Computer applications

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High Accuracy Distance Measurement with FMCW Radar and Phase Algorithm 3

High Accuracy Distance Measurement with FMCW Radar and Phase...

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3rd International Conference on Electronic Information Engineering and Computer Communication, EIECC 2023

作者： Liu, Hanyu Xu, Ding Electronic Information Engineering Institute Beihang University Beijing China

ISBN: (纸本)9798350359961

The main focus of this paper is on an indoor positioning system based on high-precision ranging. Firstly, a high-precision algorithm based on phase was studied and compared with other related algorithms. After simulation, hardware experiments were conducted to demonstrate the feasibility of achieving precise positioning for a certain object. © 2023 IEEE.

关键词： Distance measurement millimeter wave radar radar measurements radar theory signal processing algorithms

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Recovering the Parameters of an LDPC Code From Noisy Intercepted Sequences

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IEEE signal processing LETTERS 2022年 29卷 617-621页

作者： Li Longqing Shen Fangqi Zhou Jing Natl Univ Def Technol Coll Intelligent Sci Changsha 410073 Hunan Peoples R China

Blind identification of channel codes is a key technology in non-cooperative communication as well as intelligent communication. In this letter, we are interested in recovering the parameters of low-density parity-check (LDPC) codes without any a priori information. We propose to find dual codewords from noisy intercepted sequences and prove that the problem is NP-complete. Afterward, we propose an improved collision-based algorithm that can avoid most of the invalid searches and thus allowing a significant reduction in complexity. The algorithm produces almost no errors when the noise is small. While in the case of non-negligible noise, we propose to use soft information to detect the outputs of the algorithm, and errors in which can therefore be extensively eliminated. After a sufficient number of dual codewords have been found, one can easily recover the code lengths and code rates of LDPC codes, as well as the sizes of sub-matrices for Quasi-Cyclic LDPC codes. Experimental results show that the proposed method has an improved noise tolerance and can be more efficient than existing methods.

关键词： Parity check codes signal processing algorithms Noise measurement Detectors Noise level Computational complexity Buildings Blind identification dual codewords LDPC codes

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Traffic Speed Estimation Device Based on Dual-Axis Magneto-Impedance Sensors for Complex Traffic Conditions

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2025年

作者： Yao, Ruixuan Uchiyama, Tsuyoshi Nagoya Univ Dept Elect Nagoya 4648603 Japan

The development of autonomous driving has created new demands for real-time road surveillance. Portable, high-precision, low-power road infrastructure is needed to enable real-time communication of collected vehicle data with passing vehicles. Vehicle recognition and speed estimation are key challenges in this context. We propose a traffic detection device using dual-axis magneto-impedance (MI) sensors installed roadside to detect vehicles in adjacent lanes. Experiments were conducted by driving various vehicle types under a variety of complex road and traffic conditions, analyzing how different measurement conditions and driving patterns affect magnetic signatures. We identified the magnetic signatures most strongly correlated with vehicle recognition and speed estimation. We developed corresponding solutions to address issues as repeated misrecognition and the influence of non-adjacent lanes, which are frequently highlighted in related works. Ultimately, we achieved an overall recognition accuracy of 96.66% in random measurements on complex traffic conditions, reducing recognition errors related to these issues to 3.22%. Additionally, we proposed two speed estimation methods: the time-domain magnetic signature differential method and the dominant frequency method, utilizing multiple sensor nodes and a single node, respectively. Both speed estimation methods were analyzed and compared through controlled experiments, and their performance was evaluated in random measurement experiments. Both methods showed similar estimation accuracy on straight roads, with 100% and 98.8% of results falling within a +/- 5 km/h error range, respectively. In low-speed curved sections where multiple sensor nodes could not be deployed, we achieved speed estimation using a single sensor by analyzing frequency-domain signals. Finally, under complex traffic conditions, the device demonstrated a minimum Mean Absolute Error (MAE) of only 2.09 km/h for speed estimation.

关键词： Magnetic sensors Sensors Estimation Roads Accuracy Magnetic domains Real-time systems signal processing algorithms Magnetic analysis Intelligent sensors Magnetic sensor vehicle recognition speed estimation traffic surveillance

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Compressive Phaseless Imaging Based on Synthetic Aperture Radar Techniques

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2025年 74卷

作者： Vijande, Alejandro del Hoyo Alvarez-Lopez, Yuri Laviada, Jaime Andres, Fernando Las-Heras Univ Oviedo Campus Univ Gijon Dept Elect Engn Elect Commun & Syst Gijon 33203 Spain

This contribution presents a method to simplify the instrumentation required in an electromagnetic imaging system by processing scalar data. Starting from a reduced number of amplitude-only scattered field measurements, and combining phaseless algorithms with the compressive sensing (CS) framework, a reflectivity image of the region of interest (ROI) can be generated. The complexity of the system shifts from the hardware components involved in the measurement stage to the processing algorithms, allowing for the use of more cost-effective equipment. The proposed method has been tested both in simulation and measurement. In order to reach the convergence of the algorithms, the method exploits the information of the scattered field in four different planes, located at different distances from the plane containing the targets. Besides, solving the phaseless problem in terms of spatial frequency-domain basis functions allows for a significant reduction in the number of unknowns, which results in an improvement in the convergence of the phaseless iterative methods. Satisfactory results have been obtained using only 50% of the measurements required to uniformly sample the field according to the Nyquist-Shannon criterion.

关键词： Imaging Phase measurement Reflectivity Image reconstruction Compressed sensing Radar imaging Antenna measurements Synthetic aperture radar Spectral analysis signal processing algorithms Compressive sensing (CS) electromagnetic imaging phaseless imaging radar signal processing synthetic aperture radar (SAR)

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Channel Modeling and signal processing for Underwater Massive MIMO System Under Link Misalignment

Channel Modeling and Signal Processing for Underwater Massiv...

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IEEE International Symposium on Parallel and Distributed processing with Applications and IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC)

作者： Kongliang Zhu Yanlong Li Jielin Fu Guojing Peng Department of Information and Communication Guilin University of Electronic Technology Guilin China Ministry of Education Key Laboratory of Cognitive Radio and Information Processing Guilin University of Electronic Technology Guilin China

Aiming at the problem of increased interference of different light signals caused by the increase in the number of LEDs, the link misalignment of the underwater optical wireless communication (UOWC) system, and the shift and expansion of the light spot in the massive multiple in multiple out (Massive-MIMO) optical communication system, this paper uses an aspherical lens set as the receiving optical antenna to separate different beams and optimizes the lens structure to further completely separate different beams. In this paper, the Singular value decomposition based on the least-squares channel estimation (LS-SVD) precoding algorithm is used to reduce the impact of communication link misalignment on the performance of the communication system and improve the system bit error rate performance (BER). The simulation results show that the LS-SVD precoding algorithm is better than the traditional Lattice Reduction (LR) precoding algorithm, zero-forcing (ZF) detection algorithm, and the minimum mean square error (MMSE) detection algorithm under the condition of misalignment of the communication link in the underwater Massive-MIMO system, the LS-SVD precoding algorithm improves the BER by about an order of magnitude under the same signal-to-noise ratio (SNR).

关键词： Precoding Simulation Bit error rate signal processing algorithms Interference Optical fiber communication Detection algorithms

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Development of an Algorithm for Human Emotional State Correction via Electroencephalographic signal processing

Development of an Algorithm for Human Emotional State Correc...

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IEEE Region 8 International Conference on Computational Technologies in Electrical and Electronics Engineering, SIBIRCON

作者： Alexander Yu. Tychkov Sofya Yu. Tverskaya Alan K. Alimuradov Research Institute for Basic and Applied Studies Penza State University Penza Russia Department of Radioengineering and Radioelectronic Systems Penza State University Penza Russia Student Research and Production Business Incubator Penza State University Penza Russia

ISBN: (纸本)9781665464819

The present paper is aimed at developing and investigating an original algorithm for human emotional state correction using complex processing and analysis of electroencephalographic signals (EES). EES parameters have been measured in a relaxed state, in natural activity, and in six modes of audio-visual stimulation (AVS): Sleep, Learn, Energ, Create, Fun, and Special. The conducted research has evidenced cerebral hemisphere arousal in subjects (with eyes open in natural activity and in the Energ mode), which explicitly illustrates the emotional state. Emotional stability has been recorded in the Sleep and Fun modes.

关键词： Sleep signal processing algorithms Energy measurement signal processing Stability analysis IEEE 802.16 Standard

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DOA Estimation for Underwater Acoustic Array in Impulsive Noise Based on Adaptive Kernel Width Mixture Correntropy

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2025年 63卷

作者： Dai, Zehua Wu, Jinqiu Yin, Jingwei Zhang, Wenbo Qi, Xiaofei Qiao, Gang Peng Cheng Lab Dept Strateg & Adv Interdisciplinary Res Shenzhen 518055 Peoples R China Harbin Engn Univ Coll Underwater Acoust Engn Harbin 150001 Peoples R China

This article investigates a direction-of-arrival (DOA) estimation method for underwater acoustic arrays in non-Gaussian impulsive noise environments. Traditional DOA estimation methods for underwater acoustic arrays typically presume that underwater environmental noise follows a Gaussian distribution. This assumption can lead to a significant degradation in estimation accuracy, or even failure, in underwater environments where non-Gaussian impulsive noise is predominant, thereby limiting the detection capabilities of underwater acoustic arrays. To address this issue, this study employs a method based on mixture correntropy, which maximizes the mixture correntropy of the residual fitting error matrix for subspace decomposition of the received data matrix, effectively filtering out impulsive noise. Considering the signal processing performance of correntropy and mixture correntropy depends on the selection of the kernel width, this article introduces a novel adaptive method for updating the kernel width. This method updates the kernel width in each iteration based on the residual fitting error value, setting the square of the kernel width to the sum of the squares of a preset kernel width and the residual fitting error modulus. This approach retains the simplicity and robustness of the maximum mixture correntropy criterion (MMCC) algorithm while enhancing the convergence rate and achieving a lower steady-state excess mean square error. Furthermore, this study applies the classical multiple signal classification (MUSIC) algorithm for DOA estimation. Finally, simulations and sea trials have substantiated the correctness and effectiveness of the method proposed in this article.

关键词： Noise Estimation Direction-of-arrival estimation Kernel Underwater acoustics Filtering signal processing algorithms Multiple signal classification Acoustic arrays Array signal processing Adaptive kernel width direction-of-arrival (DOA) estimation mixture correntropy non-Gaussian impulsive noise underwater acoustic arrays

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Modified Time-Domain Backprojection Algorithm for SAR Frequency-Domain Autofocus

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2025年 63卷

作者： Liu, Yanqi Fan, Jixia Tao, Manyi Shi, Tianyue Mao, Xinhua Nanjing Univ Aeronaut & Astronaut Key Lab Radar Imaging & Microwave Photon Minist Educ Nanjing 211106 Peoples R China Shanghai Acad Spaceflight Technol Shanghai 201109 Peoples R China Shanghai Inst Satellite Engn Shanghai 201109 Peoples R China Nanjing Univ Aeronaut & Astronaut Shenzhen Res Inst Shenzhen 518063 Peoples R China

The backprojection (BP) algorithm is a precise time-domain technique in synthetic aperture radar (SAR) imaging, known for its robustness in scenarios where frequency-domain algorithms struggle, such as nonlinear flight paths, high-resolution demands, or large imaging swaths. However, the unknown spectral structures of BP images pose significant challenges for frequency-domain autofocus algorithms, including phase gradient autofocus (PGA). This article introduces a novel interpretation of the BP algorithm, and then compares the image spectra between BP and the polar format algorithm (PFA). Our findings indicate that BP image's spectrum suffers from severe range ambiguity and spectral misalignment, which is the key reason why BP images cannot be directly applied to PGA. To address these issues, we first improve the postprocessing method, and then propose a modified BP algorithm. Both the approaches reconstruct the signal spectrum, thereby facilitating the direct application of PGA. Compared with the postprocessing method, the proposed algorithm is more efficient. Simulation and real data experiments validate the feasibility and efficacy of the proposed method, demonstrating the proposed algorithm's suitability for autofocusing in the frequency domain.

关键词： Radar imaging Electronics packaging Frequency-domain analysis Imaging History signal processing algorithms Fourier transforms Radar polarimetry Azimuth Synthetic aperture radar Backprojection (BP) frequency-domain autofocus spectrum analysis synthetic aperture radar (SAR)

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Real-Time signal processing using AI Integrated Framework for Color and Drawing in Gesture Recognition

Real-Time Signal Processing using AI Integrated Framework fo...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Geerija Lavania Vivek Arya Neha Sharma Mamoon Rashid Shaik Vaseem Akram Artificial Intelligence & Data Science Department JECRC Jaipur Rajasthan India Dept of Electronics and Communication Engineering Gurukula Kangri (Deemed to be University) Haridwar India Chitkara University Institute of Engineering and Technology Chitkara University Rajpura Punjab India Department of Computer Engineering Vishwakarma University Pune India Uttaranchal Institute of Technology Uttaranchal University Dehradun India

In the realm of image processing and pattern recognition, writing with gestures in the air has grown in popularity and difficulty over the past few years. It contributes significantly to the creation of automation processes and can improve human-machine communication in a range of systems. Many studies focus on cutting-edge methods and techniques that will expedite processing while preserving a high level of identification accuracy. Internally, the area of computer vision considers object tracking to be crucial. Object tracking techniques are credited to modern computers, easy access to good-looking, affordable video cameras, and automated video analytics requirements. The video analysis technique generally consists of three fundamental steps: first, recognizing the object, second, tracking its movement from frame to frame, and third, assessing the behavior of that object. Each of the four takes into account a separate issue: choosing the best item representation, choosing the tracking function, purchasing the item, and tracking the item. Numerous real-world applications, such as autonomous monitoring, video identification, and vehicle navigation, depend heavily on object-tracking algorithms. This area is utilized by the research, which focuses on it to create a prospective text-to-text converter transition. This Research occasionally works as a freelance journalist. Your fingerprint will be tracked by a computer. The created text can be copied and used for a variety of things, including emails and SMS. For the deaf, it will be a potent means to establish this connection. By removing the need for writing, an efficient communication system decreases the use of the phone and laptop.

关键词： Portable computers Navigation Visual analytics signal processing algorithms Writing signal processing Real-time systems

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