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检索条件"主题词=filtering algorithms"

共 10368 条记录，以下是851-860 订阅

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MHICuS-Based Fourth-Order Active Band-Pass Filter Design Optimization

MHICuS-Based Fourth-Order Active Band-Pass Filter Design Opt...

引用

International ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI-NCON)

作者： Wattanawong Romsai Chaiyo Thammarat Sarot Hlangnamthip Deacha Puangdownreong Department of Electrical Engineering Bangkokthonburi University Bangkok Thailand Department of Electrical Engineering Southeast Asia University Bangkok Thailand

ISBN: (数字)9798331543273

ISBN: (纸本)9798331543280

In this article, the meta-hybrid intensified current search (MHICuS), one of the most efficient metaheuristic optimization techniques, is applied to optimally design the fourth-order active band-pass filter. The structure of the considered fourth-order band-pass filter aligns the Sallen-Key topology. Results obtained by the MHICuS will be compared with those obtained by the classical technique using the Butterworth filter coefficient comparison principle. As results, it was found that the fourth-order active band-pass filter designed by the MHICuS provides very satisfactory frequency response with closer to the ideal response than the classical technique using the Butterworth filter coefficient comparison principle.

关键词： Band-pass filters Resistors Capacitors Metaheuristics filtering algorithms Frequency response Topology Standards Design optimization

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CTC-Assisted LLM-Based Contextual ASR

CTC-Assisted LLM-Based Contextual ASR

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IEEE Spoken Language Technology Workshop

作者： Guanrou Yang Ziyang Ma Zhifu Gao Shiliang Zhang Xie Chen MoE Key Lab of Artificial Intelligence AI Institute X-LANCE Lab Shanghai Jiao Tong University China Alibaba Group China

ISBN: (数字)9798350392258

ISBN: (纸本)9798350392265

Contextual ASR or hotword customization holds substantial practical value. Despite the impressive performance of current end-to-end (E2E) automatic speech recognition (ASR) systems, they often face challenges in accurately recognizing rare words. Typical E2E contextual ASR models commonly feature complex architectures and decoding mechanisms, limited in performance and susceptible to interference from distractor words. With large language model (LLM)-based ASR models emerging as the new mainstream, we propose a CTC-Assisted LLM-Based Contextual ASR model with an efficient filtering algorithm. By using coarse CTC decoding results to filter potential relevant hotwords and incorporating them into LLM prompt input, our model attains WER/B-WER of $1.27 \% / 3.67 \%$ and $2.72 \% / 8.02 \%$ on the Librispeech test-clean and test-other sets targeting on recognizing rare long-tail words, demonstrating significant improvements compared to the baseline LLM-based ASR model, and substantially surpassing other related work. More remarkably, with the help of the large language model and proposed filtering algorithm, our contextual ASR model still performs well with 2000 biasing words. 1

关键词： Accuracy Heavily-tailed distribution Target recognition filtering Large language models Face recognition Interference filtering algorithms Decoding Context modeling

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Effect of Zero Attractor in Conjugate Gradient Algorithm for Sparse Systems with Impulsive Noise

Effect of Zero Attractor in Conjugate Gradient Algorithm for...

引用

International Conference on Computing and Networking Technology (ICCNT)

作者： Shila Dhande Rajib Lochan Das Department of Electronics and Communication DAIICT Gandhinagar India Department of Electronics and Computer KJSCE Mumbai India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Wireless broadband channels are usually few in number. Gaussian noise model-based adaptive filtering techniques were introduced to take advantage of channel sparsity. Nevertheless, impulsive noises are frequently heard in many sophisticated broadband communications systems. Impulsive noise causes these conventional approaches to function less well. This work proposes robust sparse adaptive filtering techniques based on the adaptive conjugate gradient (CG) with penalty function to decrease impulsive noise. Penalty functions like reweighted zero attractors (RZA) are added to the CG method to study systems with different levels of sparsity. In a setting where impulses run high, Tukey’s biweight M-estimate function is used with CG to lower the steady-state excess mean square error (EMSE), and to identify the sparse systems, reweighted zero attractor penalty along with Tukey’s biweight M-estimate function is added as a penalty function. The suggested algorithms are validated for a different level of sparse systems.

关键词： Wireless communication Adaptive systems filtering Gaussian noise Noise Mean square error methods filtering algorithms Cost function Broadband communication Steady-state

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Design and Implementation of Frame Work for Building Extraction using Fast Accurate Bilateral Filter, Fast Corner Method and Improved Gaussian Blur

Design and Implementation of Frame Work for Building Extract...

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Self Sustainable Artificial Intelligence Systems (ICSSAS), International Conference on

作者： D. Devarajan R. Rajalakshmi P. Sivakumar S. Senthilkumar M. Malathi L. Ramachandran Department of Electronics and Communication Engineering E.G.S. Pillay Engineering College Nagapattinam Tamil Nadu India Department of Electronics and Communication Engineering Ramco Institute of Technology Rajapalayam Tamil Nadu India Department of Electronics and Communication Engineering Kalasalingam Academy of Research and Education Kalasalingam University Krishnankoil Tamil Nadu India

ISBN: (数字)9798350368413

ISBN: (纸本)9798350368420

Identifying and detection of buildings from satellite imagery is beneficial in mapping, environmental training, disaster management, city planning, geo references, and studies purposes. In this paper first, Gaussian mask is used in pre-processing to avoid blurring effects in computer vision to enhance image structures at different scales then Gaussian blur smoothens irregular pixel values by excising the extreme outliers. With fast accurate bilateral filter, quality of edge preserves in buildings has been smoothened, Local key point’s extraction, dominant directions and weights were extracted to detect corners of different shaped buildings in image very quickly. Based upon weightage and correct directions in voting, Transforms applied for optimum results. We processed satellite images taken from Mumbai, Chennai cities, and Nagapattinam town and rural of Nannilam in Tamilnadu, India. Kernel density distribution become extensively utilized to find the density flow for metropolitan cities also. In results, buildings detection without shadow in 28 to 35 seconds in cities and 5 to 8 seconds in urban areas and improved accuracy of 40 % in metro and 8 % in urban than existing detection techniques.

关键词： Training Accuracy Buildings Urban planning Transforms filtering algorithms Speckle Polynomials Satellite images Time factors

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On Developing a Robust Filtered-Reference RLS Algorithm and its Application for ANC Systems Targeting Impulsive Noise Sources

On Developing a Robust Filtered-Reference RLS Algorithm and ...

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IEEE Pacific Rim Conference on Communications, Computers and Signal Processing

作者： Muhammad Tahir Akhtar Department of Electrical and Computer Engineering School of Engineering & Digital Sciences Nazarbayev University Astana Kazakhstan

ISBN: (数字)9798350362312

ISBN: (纸本)9798350362329

This paper develops a robust filtered-reference recursive least squares (RLS) algorithm for active noise control (ANC) systems targeting impulsive sources. The developed algorithm is based on a previous work exploiting an objective function showing robustness to tackle impulsive sources. The update equation in the previous algorithm incorporates a fixed step-size as a learning parameter. Furthermore, the forgetting factor (signifying the memory of least squares adaptation) is kept constant as in the traditional RLS algorithm. This paper first develops a generalized sigmoid activation function computed on the basis of internally generated error signal in the ANC system. The activation function is tuned such that it stays close to unity during the transient state and decays towards zero at the steady-state. This allows to tune the step-size as well as the forgetting factor such that the step-size parameter (the forgetting factor) is adjusted to a large value (small value) during the transient state to improve upon the convergence speed. On the other hand, the step-size parameter (the forgetting factor) is automatically tuned to a small value (large value) as the ANC system approaches the steady-state. Therefore, the proposed algorithm completely solves the trade-off situation. Extensive numerical simulations have been carried out which show the effective performance of the proposed algorithm.

关键词： Noise Signal processing algorithms filtering algorithms Numerical simulation Linear programming Robustness Mathematical models Steady-state Transient analysis Convergence

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NLOS 3-D Multi-Target Positioning Algorithm for Urban Corner Based on Multipath Information

NLOS 3-D Multi-Target Positioning Algorithm for Urban Corner...

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IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)

作者： Yang Wang Wei Zeng Xi Liao School of Communications and Information Engineering Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (数字)9798350351019

ISBN: (纸本)9798350351026

This paper proposes a non-line-of-sight (NLOS) 3D multi-target positioning algorithm based on multipath information in urban corner scenarios. Firstly, the positions of all multipath ghost points are calculated using the multipath angle of arrival (AOA) and time of arrival (TOA). Secondly, an improved K-means algorithm based on the Gaussian kernel function is proposed to filter interference ghost points and determine the refined ghost point position. Finally, a multi-target position estimation algorithm based on multipath ghost point matching is proposed to complete the multi-target position estimation. Simulation results show that the proposed algorithm can achieve high-precision NLOS multi-target 3-D positioning even in the presence of certain measurement errors.

关键词： Measurement errors Matched filters Three-dimensional displays Simulation Estimation Interference filtering algorithms Information filters Antennas and propagation Kernel

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Image Enhancement in Fundus Images using Modified Frangi Vesselness Filter in comparison with Hessian and Gaussian Filter

Image Enhancement in Fundus Images using Modified Frangi Ves...

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Networking and Communications (ICNWC), International Conference on

作者： Nanmaran R Vijai Meyyappan Moorthy Srinath R Ramasamy R Imran Javeed S Srimathi S Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Tamilnadu India Department of Advanced Computer Science and Engineering Vignan Foundation of Science and Research and Technology Guntur Andhra Pradesh India Department of ECE Ramco Institute of Technology Rajapalayam Tamilnadu India Department of Bio Technology Saveetha School of Engineering SIMATS Chennai Tamilnadu India

ISBN: (数字)9798350365269

ISBN: (纸本)9798350365276

The main aim of this work to develop image enhancement algorithm using modified vesselness filter for fundus image. Image enhancement using modified vesselness filter has been designed and compared with hessian and Gaussian filters. Performance of proposed algorithm is measured using high values of Peak Signal to Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), Normalized Correlation (NC), and Naturalness Image Quality Evaluator (NIQE). Modified frangi vesselness filter provides PSNR = 41.31db, SSIM = 92.9%, NC = 23.25%, NIQE = 30.70%. Hessian filter provides PSNR = 41.37db, SSIM = 10.85%, NC = 18.65%, NIQE = 23.64%. Gaussian filter provides PSNR = 11.33db, SSIM = 95.23%, NC = 99.24%, NIQE = 6.29%. The designed filters were tested against various noises like Gaussian, salt and pepper, speckle noise. All three filters performed good against Gaussian noise over other two types of noises. Based on the simulation results modified vesselness filter performed well when compare other two filters. Keywords: Improved Filter Design, Frangi Vesselness Filter, Hessian Filter, Gaussian Filter, Medical Image Enhancement.

关键词： Image quality Pathology PSNR Gaussian noise Simulation filtering algorithms Speckle

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Segment Routing Algorithm for Mega LEO Constellations

Segment Routing Algorithm for Mega LEO Constellations

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Electronic Information Engineering and Computer Technology (EIECT), International Conference on

作者： Jiahao Tu Jiancheng Dang Kankan Wu Linwei Li Tau Ni Shanghai Institute of Satellite Engineering Shanghai China Shanghai Aerospace Science and Technology Institute Shanghai China

ISBN: (数字)9798331528850

ISBN: (纸本)9798331528867

Against the backdrop of limited transmission resources, high latency, and diverse transmission service types within mega LEO constellation space networks, this paper proposes a segment routing algorithm tailored for mega LEO constellations. In this algorithm, the application-aware module at the satellite head node collects application-specific information, while the route calculation module employs the quadrant method to filter and compute satellite segment nodes, ultimately generating an IP packet with a path label stack. The algorithm dynamically adjusts the routing path based on various application data, optimizes QoS guarantees for routing, supports the selection of satellite segment nodes in segment routing, and effectively enhances system throughput while reducing packet loss. Simulation results indicate that the proposed routing algorithm outperforms others in latency, packet loss rate, and throughput within mega LEO constellations.

关键词： Satellites Heuristic algorithms Simulation Packet loss Quality of service filtering algorithms Routing Throughput Information filters IP networks

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Experimental Investigation of the Coordinate Estimation Algorithm for the Local Navigation System With Signals Time Division

Experimental Investigation of the Coordinate Estimation Algo...

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International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Aleksander P. Malyshev Alice O. Kozhevnikova Sergey V. Chernyh Igor B. Galuev Pavel A. Bondarev Vladislav A. Yushin Radio Systems Department National Research University “MPEI” Moscow Russian Federation

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

Alternative sources of absolute positioning to global navigation satellite systems are currently being investigated, including local navigation systems. The most promising type of signals used in local navigation systems are ultra-wideband signals. Their peculiarity is low influence of multipath propagation in case of re-reflection. The disadvantage is significant attenuation during propagation. The maximum range is 300 meters. The purpose of the work is to develop and experimentally evaluate the effectiveness of the algorithm for estimating the coordinates of the consumer taking into account the instability of the reference oscillators of all devices. As a result of the work was synthesized algorithm for estimating the coordinates of the consumer taking into account the known height of the consumer. RMS deviation of the consumer coordinates in steady state does not exceed 3 cm, The transient time is 55 clock cycles of the filter operation.

关键词： Time division multiple access Radio navigation filtering algorithms Robustness Steady-state Velocity measurement Synchronization Transient analysis Clocks Ultra wideband technology

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Communication-Efficient and Resilient Distributed Deep Reinforcement Learning for Multi-Agent Systems

Communication-Efficient and Resilient Distributed Deep Reinf...

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IEEE International Conference on Unmanned Systems (ICUS)

作者： Jietong Yao Xin Gong School of Cyber Science and Engineering Southeast University Nanjing China

ISBN: (数字)9798350384185

ISBN: (纸本)9798350384192

In this paper, we address the challenge of developing a resilient Deep Q-Network (DQN) algorithm for multi-agent systems (MASs) under Byzantine attacks. Traditional Q-learning methods suffer from significant communication overhead and limited capacity to handle high-dimensional state spaces, which restricts their scalability and effectiveness in large-scale MASs. To mitigate these issues, we propose an event-triggered resilient DQN (ET-RDQN) algorithm that reduces unnecessary communication while maintaining robustness under the environment exists adversarial agents. Our approach extends the DQN algorithm to MASs and employs the Mean-Subsequence Reduced (MSR) algorithm to filter out extreme values, ensuring that normal agents can still approximately estimate the optimal state-action values and achieve consensus even in the presence of malicious agents. The algorithm incorporates an event-triggered mechanism that triggers communication only when the triggering conditions are met, thereby reducing communication overhead. Theoretical analysis and extensive simulations demonstrate that our ET-RDQN algorithm significantly improves the resilience and efficiency of MASs in the presence of Byzantine attacks, providing a scalable and effective solution for distributed reinforcement learning in adversarial environments. Finally, we conclude this paper and outline potential directions for future work.

关键词： Q-learning Event detection Network topology Scalability filtering algorithms Approximation algorithms Deep reinforcement learning Robustness Multi-agent systems Resilience

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