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检索条件"主题词=Filtering algorithms"

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CTC-Assisted LLM-Based Contextual ASR

CTC-Assisted LLM-Based Contextual ASR

引用

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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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...

引用

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 ...

引用

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...

引用

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...

引用

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

引用

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...

引用

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...

引用

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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Aquila Optimizer-Based Filtered PID Controller Design for A Spark Ignition Engine Speed Control

Aquila Optimizer-Based Filtered PID Controller Design for A ...

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Innovative Approaches in Smart Technologies (ISAS), International Symposium on

作者： Serdar Ekinci Davut Izci Raymond Ghandour Mohammad Salman Cebrail Turkeri Department of Computer Engineering Batman University Batman Turkey College of Engineering and Technology American University of the Middle East Kuwait

ISBN: (数字)9798331540104

ISBN: (纸本)9798331540111

This paper presents a novel approach for optimizing the speed control of a four-cylinder spark ignition engine (SIE) using a filtered proportional-integral-derivative (PID) controller tuned by the aquila optimizer (AO). SIEs require precise speed control to enhance performance, fuel efficiency, and emission regulation. Traditional PID controllers, while widely employed, face significant challenges in parameter tuning due to nonlinear engine behavior. The AO, inspired by the hunting techniques of the aquila bird, effectively optimizes the controller’s parameters. Comparative simulations between AO, differential evolution (DE), grey wolf optimizer (GWO), and Simulink PID tuner show that AO achieves better performance in terms of minimizing the integral of time-weighted absolute error (ITAE). The AO-based controller delivers faster settling times and reduced overshoot, indicating its superior capability in maintaining engine stability during speed transitions.

关键词： Tuners Software packages Velocity control Ignition filtering algorithms Stability analysis Sparks Transient analysis Engines Optimization

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Additively Manufactured High-Power Light Weight Millimeter-Wave Band Pass Filter Optimized with AI Tuning Algorithm for 5G Space Applications

Additively Manufactured High-Power Light Weight Millimeter-W...

引用

Microwave, MTT-S International Symposium

作者： Laila Salman Diamond Liu Sunil Acharya Loren Vancleef Koen Huybrechts Gada Saad Mohamed Ali Ansys Inc. USA SynMatrix Technologies Inc. Canada 3D Systems Belgium SMCQ Canada

ISBN: (数字)9798350375046

ISBN: (纸本)9798350375053

High power light weight radio frequency (RF) passive components are critical for satellite communications payloads and are required to handle increasingly larger peak/average powers over the frequency range in the transmit path of the communication link. Powder-bed fusion metal additive manufacturing process has matured as a breakthrough technology for the development of arbitrary shape RF and microwave components where conventional machining can be complex or impossible to use. When it comes to space applications, industries rely on testing to mitigate system failure. Reproducing space conditions for validation in a laboratory setting is costly, time-consuming, and ultimately unreliable. Hence, leveraging the use of artificial intelligence (AI) optimization techniques in the design process of RF components is impactful. The presented work demonstrates the use of physics-based simulation technologies from modelling/synthesize to manufacturing process of an optimized millimeter-wave band pass filter that can be safely launched to space for satellite communication.

关键词： Band-pass filters Radio frequency Passive filters Millimeter wave technology Microwave communication filtering algorithms Microwave filters

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