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检索条件"主题词=Filtering algorithms"

共 10368 条记录，以下是1461-1470 订阅

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Live Demonstration: A Video Denoising Co-processor with Non-local Means Algorithm for FHD 30fps Image Sensor

Live Demonstration: A Video Denoising Co-processor with Non-...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Ruoheng Yao Shengming Zhou Zhiyue Gao Yangyi Zhang Yiwei Luo Lei Chen Fengwei An Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

In this demonstration, a non-local means (NLM) video denoising co-processor with data reuse scheme and dual-clock domain for high resolution image sensor is presented. With an OV5640 camera, the real-time denoising processor can be performed at 30 frames/second for full high definition (FHD 1920×1080) RAW video, a debayer filter then decodes the RAW format to RGB format.

关键词： Image sensors Image resolution Circuits and systems Noise reduction Streaming media filtering algorithms Cameras

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A Data Driven Correction Algorithm for Inverse Problems with Application to Spectral Reconstruction

A Data Driven Correction Algorithm for Inverse Problems with...

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IEEE SENSORS

作者： Jonathan Laubmann Stefan Saloman Julio Wissing Wladimir Tschekalinskij Sebastian Hettenkofer Alessio Stefani Teresa Scholz Integrated Sensor Systems Fraunhofer IIS Erlangen Germany DUALQUANT GmbH Nürnberg Germany

ISBN: (数字)9798350363517

ISBN: (纸本)9798350363524

Plasmonic filter arrays offer a potential solution for creating compact and cost-effective spectrometers. However, they cannot filter accurately at specific wavelengths, resulting in raw outputs that do not adequately represent the spectra of measured objects. Consequently, a process is required to reconstruct the spectra from the CSS (Chip-Size Spectrometer) values. This paper presents a novel procedure for reconstruction that employs a transformation correction of the measured CSS values before approximating the spectra. The performance of this method is compared with a deep learning architecture, as well as least squares with Tikhonov regularization and Ridge regression. This evaluation is conducted using data from two different plasmonic filter arrays and a set of measurements based on transmittance foils. The results demonstrate that our method outperforms other approaches and achieves better reconstruction accuracy compared to pure learning methods, while needing significantly less data.

关键词： Training Semiconductor device measurement Wavelength measurement Machine learning filtering algorithms Plasmons Robustness Mathematical models Sensors Sensor arrays

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Distributed recursive filter for 2-D Markov jump systems with stochastic communication protocol and nonlinearities

Distributed recursive filter for 2-D Markov jump systems wit...

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Fully Actuated System Theory and Applications (CFASTA), Conference on

作者： Fengying Ge Chunyan Han School of Electrical Engineering University of Jinan Jinan P. R. China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

This paper investigates the distributed filtering for a class of two-dimensional Markov jump parameter systems with communication protocols and nonlinearity. The system is described by the FM-II model and the random communication protocol is characterized by a set of mutually uncorrelated random processes with known probability distributions, which determines the transmission order of each sensor data. The objective is to develop a recursive distributed filter for the two-dimensional systems. Firstly, an upper bound of the local estimation error variance is established through the mathematical induction method and the stochastic analysis approach. Then, by the complete mean square method, the filter gains are derived by optimizing the upper bound of the estimation error variance. Subsequently, a distributed filter based on covariance intersection (CI) fusion algorithm is developed, which exhibits higher accuracy and reliability. Finally, a numerical example is provided to demonstrate that the fusion estimator exhibits higher estimation accuracy compared to the local one.

关键词： Estimation error Protocols Upper bound Accuracy Stochastic processes filtering algorithms Reliability theory

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Fast and Effective Satellites Selection Algorithm for Multi-Constellation GNSS Receiver Based on Incremental Greedy Approach

Fast and Effective Satellites Selection Algorithm for Multi-...

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Information, Control, and Communication Technologies (ICCT), International Conference on

作者： Raafat Ali Dept. of Multimedia Technologies and Telecommunications Moscow Institute of Physics and Technology (MIPT) Moscow Russia

ISBN: (数字)9798331517564

ISBN: (纸本)9798331517571

The combined utilization of signals from multiple constellations has become a prevailing trend in the advancement of GNSS. This paper addresses the problem of accuracy and the computational complexity for Multi-Constellation GNSS receiver. This problem is rather crucial for applications just like most of real time and SOC GNSS receiver due to the limited recourses regarding the huge number of visible and available GNSS satellites for the navigation filter algorithms. Where the traditional existed receivers either use all the available observations to estimate the user position or set some simple rules regarding some metrics or elevation angle mask, many studies analyze the optimization process and suggest smart selection algorithms. However, these methods are still costly and were not tested on real data. The method proposed in this article can reduce computational time up to 4.2 times compared to state-of-the-art algorithms at a cost of additional 6% position estimation error, as the experimental results show.

关键词： Measurement Global navigation satellite system Estimation error Satellites Costs Receivers filtering algorithms Market research Real-time systems Optimization

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Particle Filter-Based Localization Algorithm for Autonomous Robots in Smart Factories

Particle Filter-Based Localization Algorithm for Autonomous ...

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Innovative Practices in Technology and Management (ICIPTM), International Conference on

作者： Yadaiah Nirsanametla Kuldeep Sharma Kanchan Yadav A L N Rao Amit Srivastava Sanjeev Kumar Shah Chitkara Centre for Research and Development Chitkara University Himachal Pradesh India Centre of Research Impact and Outreach Chitkara University Institute of Engineering and Technology Chitkara University Rajpura Punjab India Department of Electrical Engineering GLA University Mathura Lloyd Institute of Engineering & Technology Greater Noida Lloyd Law College Greater Noida Department of Electronics & Communication Engineering Uttaranchal Institute of Technology Uttaranchal University Dehradun

ISBN: (数字)9798350307757

ISBN: (纸本)9798350307764

This research aims to study and compare the performance of four particle filter-based localization algorithms, Monte Carlo Localization (MCL), Auxiliary Particle Filter (APF), Rao-Blackwellized Particle Filter(RBPF), and FastSLAM implemented in smart factories using autonomous robots. By conducting a variety of simulations as well as real-world experiments, the paper assesses algorithmic performance in terms of accuracy computational efficiency, and responsiveness to change. FastSLAM shows itself as the best model demonstrating 0.09 of MSE and 15 ms of processing time among others. RBPF also demonstrates notable accuracy (MSE: It also focuses on its factorized state representation, accuracy, and computational efficiency. MCL and APF, which reach excellent precision and adaptive capacities, however, display slightly more computational expenses. The study offers useful information for practitioners and researchers looking for perfect solutions to robust autonomous robot localization in dynamic industrial conditions, thereby contributing towards the development of smart factory technologies.

关键词： Location awareness Accuracy Heuristic algorithms Computational modeling filtering algorithms Information filters Particle filters

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Multi-Speaker DOA Tracking Algorithm Utilizing Probability Hypothesis Density Filter and Weighted Histogram of SRP-PHAT

Multi-Speaker DOA Tracking Algorithm Utilizing Probability H...

引用

International Workshop on Acoustic Signal Enhancement (IWAENC)

作者： Yosef Soussana Elior Hadad Sharon Gannot Faculty of Engineering Bar-Ilan University Ramat-Gan Israel

ISBN: (数字)9798350361858

ISBN: (纸本)9798350361865

This contribution presents a concurrent speakers’ direction of arrival (DOA) tracking algorithm in reverberant environments. The algorithm is formulated in two stages, leveraging speech sparsity in the short-time Fourier transform (STFT) domain. In the first stage, sets of DOAs per batch of time frames are computed. Initially, a single narrow-band (NB) DOA per time-frequency (TF) bin is selected using the W-disjoint orthogonality property of speech. The NB DOA is obtained as the maximum of the steered response power phase transform (SRP-PHAT) localization spectrum at that TF bin, together with a quality measure describing the confidence in the estimation. A localization spectrum is obtained by combining the NB DOAs using a weighted histogram, with the quality measures serving as weights. The set of DOAs is determined by identifying peaks in the resulting localization spectrum. The collection of DOAs is modeled as a random finite set (RFS). In the second stage, the probability hypothesis density (PHD) filter is applied to estimate and track the speakers’ DOAs over a collection of batches. Information from the first stage is utilized to calculate prior knowledge on the appearance of new speakers. Our experimental study demonstrates the superiority of the proposed algorithm over a baseline approach.

关键词： Location awareness Weight measurement Radio frequency Histograms Time-frequency analysis Direction-of-arrival estimation Power measurement filtering algorithms Information filters Time measurement

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FA-YOLOv9: Improved YOLOv9 Based on Feature Attention Block

FA-YOLOv9: Improved YOLOv9 Based on Feature Attention Block

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International Conference on Multimedia Analysis and Pattern Recognition (MAPR)

作者： Tho-Quang Nguyen Huu-Loc Tran Tuan-Khoa Tran Huu-Phong Phan-Nguyen Tien-Huy Nguyen University of Information Technology Ho Chi Minh City Vietnam Vietnam National University Ho Chi Minh City Vietnam

ISBN: (数字)9798350368437

ISBN: (纸本)9798350368444

In educational environments, controlling students’ behaviors and gestures is a significant challenge. With the advancements in deep learning technology, utilizing videos and images for detecting behaviors, events, and objects has gained considerable attention. This research introduces a novel method to enhance the detection capability of the YOLOv9 model by integrating the Feature Extraction (FA) Block for detecting student behaviors in educational settings. With the incorporation of FA, an attention mechanism, the model can fine-tune feature representations and prioritize crucial multi-spatial and channel features. Our results highlight the effectiveness of employing attention mechanisms within deep learning frameworks for recognizing subtle behaviors. This research not only contributes to the advancement of computer vision techniques but also holds promise for practical applications in educational settings, facilitating efficient and comprehensive monitoring of student engagement and behavior. Through detailed experiments on benchmark datasets, we demonstrate the effectiveness of our fine-tuned FA-YOLOv9 model in accurately detecting diverse student behaviors. Specifically, we achieved SOTA results of 77.8% mAP50 and 74.3% Recall compared to other YOLO models.

关键词： YOLO Deep learning Analytical models Attention mechanisms Computational modeling filtering algorithms Feature extraction

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Wideband Channel Tracking with Quantization Distortion

Wideband Channel Tracking with Quantization Distortion

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International Conference on Information and Communication Technology Convergence (ICTC)

作者： Mintaek Oh Jinseok Choi Seyong Kim Jeonghun Park School of Electrical Engineering Korea Advanced Institute of Science and Technology Daejeon Republic of Korea School of Electrical and Electronic Engineering Yonsei University Seoul Republic of Korea

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

Outdated channel state information (CSI) at the base station (BS) can lead to significant performance degradation, making channel tracking crucial. In this paper, we propose a channel tracking algorithm that leverages the Bussgang decomposition and the Kalman filter to mitigate quantization distortion. Simulations demonstrate the effectiveness of the proposed algorithm under conditions of severe quantization distortion.

关键词： Quantization (signal) Acoustic distortion Noise filtering algorithms Information filters Robustness Information and communication technology Kalman filters Underwater acoustics Wideband

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Enhancing FIR Filter Design with Sequential Niching Metaheuristics: An Optimal Approach

Enhancing FIR Filter Design with Sequential Niching Metaheur...

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International Conference on Emerging Trends in Networks and Computer Communications (ETNCC)

作者： Yves Matanga Pius Owolawi Chunling Du Etienne Van Wyk School of Computer Systems Engineering Tshwane University of Technology Pretoria South Africa Tshwane University of Technology Pretoria South Africa

ISBN: (数字)9798350353266

ISBN: (纸本)9798350353273

Digital filters are routine processes in digital signal processing. Optimisation-based filter engineering ensures the precise design of filters that match the expected ideal filter profile as accurately as possible, unlike approximation methods. Considering recent developments in globally convergent niching optimisation, the current study proposes sequential niching optimisation for digital filter design to enhance the accuracy of filter profiles. Niching optimisation searches for multiple optimum solutions simultaneously, leading to a deterministic increase in diversity and a higher probability of obtaining a much-improved solution. The sequential niching optimisation framework proposed in this study has been compared against representative classical metaheuristics, yielding improved frequency response on filter design. Among the three metaheuristics compared-genetic algorithm, particle swarm optimisation and differential evolution-sequential niching differential evolution yielded a superior frequency response with the lowest ripple noise in the filter passband and 42% average improvement in solution quality over the best performing competing metaheuristic. This niching framework may be adapted to any metaheuristic algorithm of note.

关键词： Matched filters Finite impulse response filters Metaheuristics Noise Merging Signal processing algorithms filtering algorithms Frequency response Passband Particle swarm optimization

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Robust Near-field Beam Tracking via Deep Q-network for THz Communications

Robust Near-field Beam Tracking via Deep Q-network for THz C...

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International Conference on Information Fusion

作者： Hyunwoo Park Hyeonjin Chung Andrea Conti Moe Z. Win Sunwoo Kim Department of Electronic Engineering Hanyang University Seoul South Korea Department of Engineering and CNIT University of Ferrara Via Saragat 1 Ferrara Italy Laboratory for Information and Decision Systems Massachusetts Institute of Technology Cambridge MA USA

ISBN: (数字)9781737749769

ISBN: (纸本)9798350371420

This paper presents a robust near-field (NF) beam tracking algorithm for terahertz communications based on deep Q-network (DQN). Traditional NF beam tracking methods relying on mobility models are fatal in ultra-massive MIMO systems, where even the slightest error could result in beam tracking failures. Thus, the proposed algorithm aims to maintain a stable beamforming gain by tracking the mobile station through the analysis of received signals without requiring mobile dynamics. By utilizing DQN, the proposed algorithm strengthens its tracking capability from online experiences and updates the combining beam towards positions expected to maximize beamforming gain. Throughout simulations, we compare the proposed algorithm with the Bayesian filter-based NF beam tracking algorithm. The simulation results confirm the robustness of the proposed algorithm for NF beam tracking, especially for abrupt changes in mobile dynamics.

关键词： Array signal processing Mobility models Heuristic algorithms Simulation filtering algorithms Robustness Bayes methods Noise measurement MIMO communication Terahertz communications

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