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检索条件"主题词=Signal Processing Algorithms"

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Web Guardian: Harnessing Web Mining to Combat Online Terrorism

Web Guardian: Harnessing Web Mining to Combat Online Terrori...

引用

signal processing, Computation, Electronics, Power and Telecommunication (IConSCEPT), International Conference on

作者： Prerna Sharma Prakhranshu Singh C.N.S. Vinoth Kumar Department of Networking and Communications School of Computing SRM Institute of Science and Technology Kattankulathur Chennai Tamil Nadu India Department of Networking and Communications School of Computing SRM Institute of Science and Technology Kattankulathur Tamil Nadu India

ISBN: (数字)9798331540685

ISBN: (纸本)9798331540692

In recent years, terrorism has surged dramatically in specific regions, demanding immediate intervention to prevent its destructive impact on lives and property. Exploiting technological advancements, particularly the internet, terrorist groups utilize online platforms to spread propaganda, defame individuals, and recruit members for criminal activities. To effectively create a system, it is essential to use both web mining and data mining approaches to combat this danger. Web mining involves using several techniques for text mining to derive valuable insights from unorganized data. At the same time, data mining algorithms handle organized datasets, enhancing web mining's ability to navigate the intricacies of online material. However, the diverse data structures of websites pose challenges for unified algorithms. Web data mining assumes a critical role in detecting online terrorism spread, especially through the proliferation of phishing websites used for recruitment and coordination. By employing machine learning algorithms such as AdaBoost, SVM, Gradient Boosting and Random Forest, web data analysis can differentiate between legitimate and terrorist-associated sites by extracting features such as URL structure and domain age. Rigorous evaluation ensures the accuracy of these methods, enabling proactive measures like blocking identified terrorist activity sites. Through ongoing research and refinement, machine learning-driven web data mining emerges as a potent tool in combating the online dissemination of terrorist propaganda, reinforcing global security efforts.

关键词： Uniform resource locators Support vector machines Machine learning algorithms Terrorism Prevention and mitigation signal processing algorithms Web mining

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Mittag-Leffler Filter and Its Application in Bio-signals processing*

Mittag-Leffler Filter and Its Application in Bio-signals Pro...

引用

signal processing algorithms, Architectures, Arrangements and Applications (SPA)

作者： Ivo Petráš Faculty of BERG st. Letná 1/9 Technical University of Košice Košice Slovak Republic

ISBN: (数字)9788362065486

ISBN: (纸本)9798350373806

This contribution introduces a novel variant of the well-known low-pass Gaussian filter, the Mittag-Leffler filter, applicable in 1D and 2D contexts. This new filter incorporates a Mittag-Leffler function within its probability density function. It features three tunable parameters that adjust the curve shape and the filter’s forgetting factor. Illustrative examples involving two real ECG signals (one male and one female) and a real MRI image (female) highlight the main advantages of the proposed filter in comparison to the traditional Gaussian filtering (denoising) technique. Implementation details and the Matlab functions for the proposed 1D and 2D filters are provided too.

关键词： Filtering Shape Magnetic resonance imaging Noise reduction Low-pass filters signal processing algorithms Filtering algorithms Electrocardiography Probability density function MATLAB

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Consistent Spectrogram Separation from Nonstationary Mixture

Consistent Spectrogram Separation from Nonstationary Mixture

引用

European signal processing Conference (EUSIPCO)

作者： Marina Krémé Adrien Meynard Mines Saint-Etienne Institut Henri Fayol Saint-Etienne France Laboratoire de Physique Univ Lyon ENS de Lyon CNRS Lyon France

ISBN: (数字)9789464593617

ISBN: (纸本)9798331519773

We present a spectrogram separation method tailored for mixtures comprising two nonstationary components. By exploiting the unique characteristics of their time-frequency representations, we propose an inverse problem formulation to estimate the spectrograms of the components. We then introduce an alternating optimization algorithm that ensures the consistency of the estimated spectrograms. The efficacy of the algorithm is evaluated through testing on synthetic mixtures and is applied to a bioacoustic signal.

关键词： Time-frequency analysis Inverse problems signal processing algorithms Europe Spectrogram Optimization Testing

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Estimating Response of Fractional Order Systems and Control: An Orthogonal HF-BasedApproach

Estimating Response of Fractional Order Systems and Control:...

引用

IEEE International Conference on signal processing, Information, Communication & Systems (SPICSCON)

作者： Srimanti Roychoudhury Ubaidur Rahman Md. Shakawat Hossain Rabbi Department of EEE Daffodil International University Dhaka Bangladesh

ISBN: (数字)9798331510213

ISBN: (纸本)9798331510220

In an attempt to simplify the mathematical solution of real-world systems, further presumptions such as an integer order system and zero initial condition lead to imprecise and incorrect system modeling. By modeling real-world systems with fractional orders these problems can be solved with more accuracy. However, analyzing those systems and determining time-based responses are quite difficult challenges. Several techniques for fractional order system approximation were developed earlier and are accessible in the literature to reduce the mathematical complexity. However, the proposed method for solving the issue is more efficient and provides far more accurate results with a simpler algorithm than existing methods. Based on the orthogonal hybrid functions (HF), the suggested method is found. When working with function samples, the orthogonal HF set can efficiently provide piecewise linear solutions for a variety of control systems. A few examples are included with pertinent figures and tables, and the findings are compared using current methodologies to verify the accuracy of the solution and the efficacy of the method being discussed.

关键词： Accuracy signal processing algorithms Hafnium Systems modeling signal processing Approximation error Control systems Approximation algorithms Mathematical models Time factors

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Multichannel Sparse Recovery for Constant Modulus signals via ℓ∞,1 Minimization

Multichannel Sparse Recovery for Constant Modulus Signals vi...

引用

signal, Information and Data processing (ICSIDP), IEEE International Conference on

作者： Yi-Lin Mo Zai Yang Wenlong Wang Xunmeng Wu School of Mathematics & Statistics Xi’an Jiaotong University Xi’an China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Compressed sensing techniques have been extensively studied over recent decades, finding broad applications in signal processing. Convex optimization approaches for compressed sensing, such as l 2,1 -minimization, are employed for recovering sparse signals in multichannel scenarios. However, when joint sparse signals also exhibit the constant modulus (CM) property, l 2,1 -minimization fails to exploit this prior information. In this paper, we focus on utilizing l ∞,1 -minimization to recover sparse signals with the CM property. For this convex optimization method, a fast algorithm based on the alternating direction method of multipliers is proposed. Extensive numerical simulations are carried out to demonstrate the effectiveness of l ∞,1 -minimization for CM signal recovery.

关键词： signal processing algorithms signal processing Numerical simulation Minimization Data processing Convex functions Sensors Compressed sensing

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Radar-Based Breathing Sensor for Child Presence Detection in Automotive Applications

Radar-Based Breathing Sensor for Child Presence Detection in...

引用

Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Jonas Gillner Roy Taylor Klaus Thelen Measurement & Sensor Technology Ruhr West University of Applied Science Muelheim Germany Electrical and Computer Engineering Wayne State University Detroit MI USA

ISBN: (数字)9798350387179

ISBN: (纸本)9798350387186

This study presents a novel sensor system aimed at preventing child heatstroke in unattended vehicles. The developed system integrates a 24 GHz Continuous Wave (CW) radar, engineered to detect the subtle breathing signals of infants. A custom-designed 4- by −1 patch array antenna, optimized for this specific application, is seamlessly embedded into a designed PCB. To enhance efficiency and accuracy, the system incorporates a low-cost 8-bit Microcontroller (MC) and a dedicated hardware filter. These components facilitate a tailored signal processing algorithm specifically designed for efficient and rapid computation of the child's Respiratory Rate (RR). The system's performance evaluation involved monitoring a sleeping infant's respiratory patterns in real-time. Collected data was then compared against established reference standards to assess the system's accuracy in detecting the child's RR, providing compelling evidence of its efficacy. Furthermore, the system has demonstrated compliance with automotive industry standards, assuring seamless integration into existing vehicle frameworks. This innovation holds significant potential to proactively enhance automotive safety standards.

关键词： Pediatrics Accuracy Vehicle safety signal processing algorithms Radar detection Radar Radar antennas

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Rx DSP-based Estimation for MPI in PAM4-DD Short Reach Optical Transmission System

Rx DSP-based Estimation for MPI in PAM4-DD Short Reach Optic...

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OptoElectronics and Communications Conference, OECC

作者： Jin Zhu Jiahao Huo Jianlong Tao Xiaoying Zhang Peng Qin Xian Zhou Wei Huangfu Keping Long University of Science and Technology Beijing Beijing China

The four-level pulse amplitude modulation (PAM4) signal is highly susceptible to MPI in short reach optical intensity modulation direct detection (IM-DD) systems. This paper addressed the problem by employing two Rx s... 详细信息

ISBN: (数字)9798350308396

ISBN: (纸本)9798350308402

关键词： Simulation signal processing algorithms Estimation Digital signal processing Interference Amplitude modulation Intensity modulation Optical signal processing Optical pulses

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Hardware Implementation of Area-Time Efficient Modular Multiplication over NIST Prime Fields

Hardware Implementation of Area-Time Efficient Modular Multi...

引用

IEEE International Conference on signal processing, Information, Communication & Systems (SPICSCON)

作者： Md. Sazedur Rahman Ibnul Zarrah Kalyan Kumar Halder Department of Electrical and Electronic Engineering Khulna University of Engineering & Technology Khulna Bangladesh Department of Electrical and Electronic Engineering Hajee Mohammad Danesh Science and Technology University Dinajpur Bangladesh

ISBN: (数字)9798331510213

ISBN: (纸本)9798331510220

This research presents an efficient modular multipli-cation for elliptic curve cryptography (ECC) over NIST prime fields. The development of ECC processors that can perform modular multiplication while minimizing hardware utilization is a crucial need in cryptography and cybersecurity. The efficiency of modular multiplication is a key factor that directly impacts the overall performance of ECC processors. Achieving fast modular multiplication with low hardware usage involves optimizing the design of ECPs to balance computational speed, resource utilization, and resistance to side-channel attacks. Our proposed design aims to achieve higher performance with reduced power consumption. For performance evaluation, we synthesized our design on various FPGA platforms, including Virtex-7 and Virtex-6, using different NIST primes. The mostly used 256-bit modular multiplication device utilization is reduced greatly here, and we extend this work to higher bits, i.e., 384-bit and 521-bit NIST primes.

关键词： Performance evaluation Program processors signal processing algorithms Computer architecture Side-channel attacks NIST signal processing Elliptic curve cryptography Hardware Field programmable gate arrays

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Deep Unfolding-Based Channel Estimation and Soft Symbol Decoding with Low-Resolution ADCs

Deep Unfolding-Based Channel Estimation and Soft Symbol Deco...

引用

European signal processing Conference (EUSIPCO)

作者： Sahil Katyal Sameera Bharadwaja H. Chandra R. Murthy Indian Institute of Science Bengaluru India

ISBN: (数字)9789464593617

ISBN: (纸本)9798331519773

This work develops a deep unfolding-based variational Bayes (VB) technique called learned-Vb for joint channel estimation and data decoding using quantized inputs in a massive multi-input multi-output (MIMO) uplink system. The unfolded neural network learns the channel statistics using self-training. The training process does not explicitly optimize to reduce the difference between the actual and estimated channel statistics. Instead, a linear combination of cross-entropy loss between the true and the soft data symbols and the mean squared error loss between the true and the estimated channel is minimized. The performance of the proposed algorithm is studied and compared against a channel statistics-aware VB algorithm under both i.i.d. and correlated channel models. It is found that the deep unfolding model overcomes the dependency on the knowledge of the channel statistics, thus making the approach suitable for unknown or mismatched channel statistics. Specifically, the unfolding-based method performs on par with the vanilla VB inference (VBI) algorithm when the latter has exact knowledge of the channel statistics while offering much better performance when the channel statistics are mismatched.

关键词： Training Neural networks Channel estimation Symbols signal processing algorithms Transformers Inference algorithms Decoding Uplink signal to noise ratio

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Optimal Design of RDARS-aided Multi-user Systems with Low-resolution DACs

Optimal Design of RDARS-aided Multi-user Systems with Low-re...

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IEEE Workshop on signal processing Advances in Wireless Communications (SPAWC)

作者： Jintao Wang Chengzhi Ma Shaodan Ma Department of Electrical and Computer Engineering State Key Laboratory of Internet of Things for Smart City (SKL-IOTSC) University of Macau Macao SAR China

ISBN: (数字)9798350393187

ISBN: (纸本)9798350393194

Recently, a flexible reconfigurable architecture called reconfigurable distributed antenna and reflecting surface (RDARS), which maintains the advantages of distributed antennas while reducing hardware costs, has been proposed. In this paper, we investigate the appealing benefits of the RDARS’s architecture by considering an RDARS-aided downlink communication system under the limited resolution of digital-to-analog converters (DACs) and phase shifts. The dynamic selection of the reflection/connection modes at the RDARS and the reflective phase coefficients are optimized to maximize the communication rate. To tackle the mix-integer optimization problem, an inexact block coordinate descent (BCD) algorithm is then proposed. Numerical simulations demonstrate great superiority for the proposed RDARS-aided architecture as compared to the conventional benchmarks and show potential benefits in compensating for the limited resolution of hardware.

关键词： Wireless communication Heuristic algorithms Transmitting antennas signal processing algorithms Benchmark testing Reflector antennas Downlink Hardware Surface treatment Antenna arrays

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