检索结果-内蒙古大学图书馆

Hilbert-Huang Transform With Intelligent Noise Reduction for Passive SONAR signal processing

IEEE JOURNAL OF OCEANIC ENGINEERING 2025年第2期50卷 1387-1402页

作者： Sarno Filho, Elio Pithon Santos, Anderson Damacena Simas Filho, Eduardo F. Fernandes Jr, Antonio Carlos Lopes de Seixas, Jose Manoel de Moura Jr, Natanael N. Univ Fed Bahia Elect Engn Program BR-40170110 Salvador BA Brazil Univ Fed Rio de Janeiro Signal Proc Lab COPPE POLI BR-21941853 Rio De Janeiro Brazil

Ocean science plays a key role in marine exploration, encouraging the development of new methods for analyzing underwater acoustic waves. In passive SOund NAvigation and Ranging (SONAR) signal processing for military vessel detection and classification, the predominant technique is the short-time Fourier transform (STFT). However, this spectral analysis method has time-frequency (TF) resolution limitations, impacting performance in feature extraction and vessel dynamic behavior monitoring. The Hilbert-Huang transform (HHT) is an alternative to STFT, providing a data-driven TF analysis with high resolution. However, in standard HHT algorithms, estimation accuracy degrades as noise increases. This article presents a novel algorithm for HHT that computes the HHT with intelligent noise removal (HHT-INR). The proposed method is focused on passive SONAR surveillance applications, in which the information of interest usually comprises different sinusoidal components produced by the vessels' machinery and propeller system. An intelligent system based on support vector machine detects and removes noisy IMF during the EMD estimation process. Results with simulated and experimental passive SONAR signals indicate better performance than the STFT-based analysis. The HHT-INR reduces background noise and enhances resolution for analyzing vessel parameters in time-varying scenarios. The proposed method significantly improved frequency resolution in experimental signals, achieving an average reduction in spectral width of approximately 28.5 times. In addition, there was an average increase of 87.9 dB in the signal-to-noise ratio.

关键词： Noise Sonar navigation Noise reduction Support vector machines Sonar detection Propellers Estimation Wavelet transforms signal processing algorithms Noise measurement Hilbert-Huang transform (HHT) intelligent classification system passive sound navigation and ranging (SONAR) support vector machine (SVM) underwater acoustic signal (UAS) processing

来源：评论

学校读者我要写书评

暂无评论

Advanced Near-Field Radar Imaging Approaches in Security: An overview on signal processing challenges, opportunities, and future directions

引用

IEEE signal processing MAGAZINE 2025年第1期42卷 126-146页

作者： Molaei, Amir Masoud Hu, Shaoqing Fusco, Vincent Fromenteze, Thomas Kumar, Rupesh Abbasi, Muhammad Ali Babar Yurduseven, Okan Queens Univ Belfast Ctr Wireless Innovat Belfast BT3 9DT North Ireland Brunel Univ London Coll Engn Design & Phys Sci Uxbridge UB8 3PH England Hangzhou Dianzi Univ Sch Elect & Informat Hangzhou 310005 Peoples R China Univ Limoges Xlim Res Inst F-87000 Limoges France Duke Univ Ctr Metamat & Integrated Plasmon Durham NC 27705 USA SRM Univ Andhra Pradesh Dept Elect & Commun Engn Amaravati 522502 Andhra Prades India

Near-field (NF) microwave and millimeter-wave (mm-wave) imaging, extending into the terahertz (THz) frequency range, has seen remarkable advancements across diverse applications, particularly security screening. These technologies benefit from the unique properties of microwave, mm-wave, and THz (MMT) spectra, such as penetration, nonionizing radiation, material sensitivity and the capability to operate in all weather conditions. This article provides an overview of the evolution and current state of NF radar imaging, emphasizing the critical role of signal processing in overcoming challenges related to hardware complexity, long acquisition time, and image reconstruction quality. Advanced signal processing techniques-including Fourier-based algorithms, sparse imaging, low-rank matrix recovery, and deep learning-are highlighted for their contributions to enhancing image resolution and processing efficiency. The article also discusses recent innovations in antenna technologies, aperture configurations, and scanning methods that have significantly improved NF radar imaging capabilities. Future research directions are suggested to further advance the field, highlighting the importance of continued exploration and innovation in NF MMT imaging.

关键词： Technological innovation Microwave technology Imaging signal processing algorithms Terahertz radiation Radar imaging signal processing Noise measurement Security Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

Distributed algorithms for Array signal processing

引用

IEEE TRANSACTIONS ON signal processing 2021年 69卷 4607-4622页

作者： Chen, Po-Chih Vaidyanathan, P. P. CALTECH Dept Elect Engn Pasadena CA 91125 USA

Distributed or decentralized estimation of covariance, and distributed principal component analysis have been introduced and studied in the signal processing community in recent years, and applications in array processing have been indicated in some detail. Inspired by these, this paper provides a detailed development of several distributed algorithms for array processing. New distributed algorithms are proposed for DOA estimation methods like root-MUSIC, total least squares-ESPRIT, and FOCUSS. Other contributions include distributed design of the Capon beamformer from data, and distributed implementation of the spatial smoothing method for coherent sources. A distributed implementation of a recently proposed beamspace method called the convolutional beamspace (CBS) is also proposed. The proposed algorithms are fully distributed - an average consensus (AC) is used to avoid the need for a fusion center. The algorithms are based on a recently reported finite-time version of AC which converges to the exact solution in a finite number of iterations. Numerical examples are given throughout the paper to show the effectiveness of the proposed algorithms.

关键词： Estimation Direction-of-arrival estimation Distributed algorithms Array signal processing signal processing algorithms Convergence Smoothing methods Distributed or decentralized DOA estimation Capon beamforming convolutional beamspace root-MUSIC ESPRIT FOCUSS spatial smoothing

来源：评论

学校读者我要写书评

暂无评论

Theory and algorithms for Pulse signal processing

引用

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2020年第8期67卷 2707-2718页

作者： Nallathambi, Gabriel Principe, Jose C. Vital Connect Inc San Jose CA 95110 USA Univ Florida Dept Elect & Comp Engn Gainesville FL 32611 USA

The integrate and fire converter (IFC) transforms an analog signal into a train of biphasic pulses. The pulse train has information encoded in the timing and polarity of pulses. While it has been shown that any finite bandwidth analog signal can be reconstructed from these pulse trains with an error as small as desired, there is a need for fundamental signal processing techniques to operate directly on pulse trains without signal reconstruction. In this paper, the feasibility of performing online the operations of addition, multiplication, and convolution of analog signals using their pulses train representations is presented. The theoretical framework to perform signal processing with IFC pulse trains imposing minimal restrictions is derived, and algorithms for online implementation of the operators is developed. The performance of the proposed algorithms is studied by quantifying the variations in instantaneous occurrence of pulses. Comparisons are performed with digital processing of reconstructed pulse trains. Moreover, an application of noise subtraction and representation of relevant features of interest in electrocardiogram signal is demonstrated with a sparse data rate of less than 20 IFC pulses per second, and an absolute error in heart rate of 0.16 +/- 0.18 bpm.

关键词： signal processing algorithms Convolution Timing Bandwidth Sensors Internet of Things Analog to pulse converter biphasic pulse trains convolution pulse signal processing semantic information

来源：评论

学校读者我要写书评

暂无评论

signal processing and Machine Learning with Differential Privacy [algorithms and challenges for continuous data]

引用

IEEE signal processing MAGAZINE 2013年第5期30卷 86-94页

作者： Sarwate, Anand D. Chaudhuri, Kamalika Toyota Technol Inst Chicago IL 60637 USA Univ Calif San Diego Dept Comp Sci & Engn San Diego CA 92103 USA

Private companies, government entities, and institutions such as hospitals routinely gather vast amounts of digitized personal information about the individuals who are their customers, clients, or patients. Much of this information is private or sensitive, and a key technological challenge for the future is how to design systems and processing techniques for drawing inferences from this large-scale data while maintaining the privacy and security of the data and individual identities. Individuals are often willing to share data, especially for purposes such as public health, but they expect that their identity or the fact of their participation will not be disclosed. In recent years, there have been a number of privacy models and privacy-preserving data analysis algorithms to answer these challenges. In this article, we will describe the progress made on differentially private machine learning and signal processing.

关键词： Privacy Data privacy signal processing algorithms Approximation methods Noise measurement Computer security

来源：评论

学校读者我要写书评

暂无评论

Learning algorithms and signal processing for Brain-Inspired Computing

引用

IEEE signal processing MAGAZINE 2019年第6期36卷 12-15页

作者： Simeone, Osvaldo Rajendran, Bipin Gruning, Andre Eleftheriou, Evangelos S. Davies, Mike Deneve, Sophie Huang, Guang-Bin Kings Coll London Dept Engn Informat Engn Res London England New Jersey Inst Technol Newark NJ 07102 USA New Jersey Inst Technol Elect & Comp Engn Newark NJ 07102 USA IBM TJ Watson Res Ctr New York NY USA Univ Surrey Dept Comp Sci Computat Intelligence Surrey England Univ Bern Inst Physiol Bern Switzerland IBM Res Zurich Zurich Switzerland Intels Neuromorph Comp Lab Zurich Switzerland Nanyang Technol Univ Sch Elect & Elect Engn Singapore Singapore

The articles in this special section focuses on machine learning (ML) and signal processing algorithms for bio-inspired computing. The articles bring together key researchers in this area to provide readers of IEEE signal processing Magazine with up-to-date and survey-style articles on algorithmic, hardware, and neuroscience perspectives on the state-of- the-art aspects of this emerging field.

关键词： Special issues and sections Bio-inspired computing signal processing algorithms Neuromorphic engineering Neuroscience Machine learning

来源：评论

学校读者我要写书评

暂无评论

FAST algorithms FOR ESTIMATION AND signal-processing - AN INVERSE SCATTERING FRAMEWORK

引用

IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND signal processing 1989年第6期37卷 957-959页

作者： YAGLE, AE Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA

The inverse scattering problem for a lossless transmission line has been used as a framework for deriving the Levinson and Schur fast algorithms for Toeplitz matrices. Here, the same framework is used to derive and attach novel simple scattering interpretations to the lattice algorithm and the split algorithms. This demonstrates that the scattering and interpretation is more fundamental to fast signal-processing algorithms than previously noted.< >

关键词： signal processing algorithms Inverse problems Speech enhancement Acoustic scattering Speech coding Filtering Filters Equations Transmission line matrix methods Phase change materials

来源：评论

学校读者我要写书评

暂无评论

A DIGITAL signal-processing ARCHITECTURE FOR ITERATIVE DECONVOLUTION RESTORATION algorithms

引用

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 1992年第1期41卷 147-151页

作者： WHITTED, RB CRILLY, PB Communications Information and Signal Processing (CISP) Group Department of Electrical and Computer Engineering University of Tennessee Knoxville Knoxville TN USA

This paper will present a VLSI DSP chip that will significantly improve the processing throughout for a general class of iterative deconvolution algorithms. The design will be based on a systolic array concept. This will enable these algorithms to be used for real-time DSP applications which formerly, due to speed limitations, were not possible. The increased class of applications will enable further understanding of these applications. The higher throughout will also enable the researcher to further take advantage of the features unique to iterative deconvolution.

关键词： Digital signal processing Deconvolution signal restoration signal processing algorithms Iterative algorithms Wiener filter Digital signal processing chips Throughput Spectroscopy Additive noise

来源：评论

学校读者我要写书评

暂无评论

signal processing of Images for Convective Boundary Layer Height Estimation From Radar (SPICER) and Multi-Instrument Verification

引用

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2025年 63卷

作者： Della Porta, Delia Tatiana Demoz, Belay Univ Maryland Baltimore Cty Dept Comp Sci & Elect Engn Baltimore MD 21250 USA Univ Maryland Baltimore Cty Dept Phys Baltimore MD 21250 USA

The study of the planetary boundary layer (PBL) is one of the main topics of the atmospheric community. This study presents a new algorithm for PBL height determination using a publicly available but unexplored data source, the Weather Surveillance Radar (WSR-88D). The diurnal evolution of the PBL is also known as the convective boundary layer (CBL), key in the study of convection and precipitation. This article presents the signal processing of Images for Convective Boundary Layer Height Estimation From Radar (SPICER) algorithm that can automatically detect the CBL height (CBLH) for all 159 radar locations across the United States during clear days. This work is the first step to applying SPICER to a network of Next-Generation Radars (NEXRAD) with continuous countrywide coverage. With the possible combination with the Automated Surface Observing System (ASOS) network, a source of ceilometer profile data, a validated dataset of CBLH estimates can be expected soon. The algorithm treats averaged differential reflectivity versus range as an image and applies filtering plus Canny edge detection to estimate the CBLH. In addition, another algorithm is presented to automate the detection of the mixing layer height (MLH), a proxy for CBLH from Raman LiDAR, and a 915-MHz wind profiler. A comparison of CBLH estimates versus widely used methods in meteorology [radiosondes, Raman LiDAR, ceilometer, 915-MHz wind profiler, and Doppler LiDAR-based derived value-added product (VAP)] is performed to validate the NEXRAD-detected CBLH using SPICER. The SPICER algorithm shows over 0.9 correlation with radiosonde measurements.

关键词： Instruments Atmospheric measurements signal processing algorithms Meteorology Laser radar Extraterrestrial measurements Reflectivity Measurement by laser beam Pollution measurement Estimation Atmospheric radiation measurement (ARM) value-added product (VAP) Bragg scattering Canny edge detection ceilometer convective boundary layer (CBL) height (CBLH) estimation differential reflectivity filtering LiDAR mixing layer height (MLH) multi-instrument CBL nationwide coverage Next-Generation Radars (NEXRAD) planetary boundary layer (PBL) PBL height (PBLH) quasi vertical profiles (QVPs) radiosondes Raman LiDAR signal-to-noise ratio (SNR) signal processing of Images for Convective Boundary Layer Height Estimation From Radar (SPICER) wind profiler Weather Surveillance Radar (WSR-88D)

来源：评论

学校读者我要写书评

暂无评论

Editorial on the Special Section on algorithms, Circuits, and Systems for signal processing at the Edge

IEEE OPEN JOURNAL OF CIRCUITS AND SYSTEMS

引用

IEEE OPEN JOURNAL OF CIRCUITS AND SYSTEMS 2021年 2卷 766-768页

作者： Sousa, Leonel Sheikh, Farhana Bermak, Amine Univ Lisbon Inst Super Tecn INESC ID Lisbon Portugal Intel Corp Santa Clara CA 95054 USA Hamad Bin Khalifa Univ Coll Sci & Engn Ar Rayyan Qatar

Technological trends alongside with the unprecedented growth of the data generated by devices sparsely distributed, most of them mobile devices, cannot be supported by traditional approaches and processing systems. The requirement for computations at the edge are very stringent in terms of security, bandwidth, computational speed, latency and power consumption. These computations typically require signal processing algorithms running on resource-constrained mobile devices, while to provide the core services and the required computational power, cloud servers are applied. Leveraging services of cloud by mobile devices result in high latency and communication network and mobility-related issues, which can be mitigated by cleverly moving some of these computation to the edge. This special Section is exactly focused on addressing challenges raised by moving computation to the edge in a holistic way, by examining not only challenges related to algorithmic consideration and computational requirements but also circuits and systems and hardware platforms suitable for such implementation. The special Section also considers the trade-offs related to power and energy consumption, bandwidth versus computational complexity and security.

关键词： Special issues and sections Edge computing signal processing algorithms Energy consumption Power demand Mobile handsets Distributed databases

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：