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检索条件"主题词=Filtering algorithms"

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Multi-Region Attention Residual Network-Based Crop Row Detection For Agricultural Robot Field Navigation

Multi-Region Attention Residual Network-Based Crop Row Detec...

引用

Artificial Intelligence, Robotics, and Communication (ICAIRC), IEEE International Conference on

作者： Ziyan Li Zhaowei Wang School of Intelligent Manufacturing Shanghai Zhongqiao Vocational and Technical University Shanghai China

ISBN: (数字)9798331531225

ISBN: (纸本)9798331531232

In the context of real-world agricultural settings, robots frequently encounter uneven terrain when navigating through tilled fields. Such irregularities can lead to the robot drifting off course. To achieve effective autonomous navigation for agricultural robots, it is crucial to develop strategies for accurately detecting crop rows to mitigate the impact of external disturbances. In this paper, a novel algorithm of crop row detection for field robots that incorporates a multi-head attention mechanism and Res-Net model is presented (MRA-ResNet). First, real-time field video captured by an agricultural robot is processed for frame extraction to obtain a large number of images, which are initially convolved by an adaptive threshold filter to obtain key frame features. Then, the crop features in the field are learned by setting up a multi-region attention module, segmenting the crop and background, and dividing the learned crop feature images into several vertical image strips. These learned vertical image strips are then mapped to the low latitude for classification by vertical projection and MRA-ResNet. Finally, the center-line of the crop rows is further determined accurately. The experimental results show that MRA-ResNet can well realize crop row detection in the field.

关键词： Agricultural robots Adaptation models Strips Navigation Noise Crops filtering algorithms Streaming media Feature extraction Real-time systems

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Joint Design of Transmit Waveform and Receive Filter for Deceptive Jammer Suppression with FDA-MIMO Radar

Joint Design of Transmit Waveform and Receive Filter for Dec...

引用

IEEE International Conference on Radar

作者： Jiawei Qi Lan Guisheng Liao National Key Laboratory of Radar Signal Processing Xidian University Xi’an China

ISBN: (数字)9798350362381

ISBN: (纸本)9798350362398

This paper considers the joint design of transmit waveform and receive filter for FDA-MIMO radar in the presence of the deceptive jammers. In our system design, the problem is formulated to maximize the Signal-to-Interference-plus-Noise Ratio (SINR) while incorporating constant modulus and similarity constraints. Specifically, for the emerged non-convex waveform optimization problem, an iterative algorithm based on the Majorization-Minimization (MM) framework is proposed to approximate the optimal solution. Furthermore, a projection algorithm is developed to eliminate the constraints. Finally, numerical simulation results illustrate that the proposed method can efficiently suppress the deceptive jammers by evaluating the SINR performance, similarity to the reference waveform, and beampattern.

关键词： Simulation Interference filtering algorithms Radar applications Iterative methods Jamming Projection algorithms Optimization System analysis and design Signal to noise ratio

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Output-Only Identification of Lur'e Systems with Hysteretic Feedback Nonlinearities

Output-Only Identification of Lur'e Systems with Hysteretic ...

引用

American Control Conference (ACC)

作者： Riley J. Richards Yulong Yang Juan A. Paredes Dennis S. Bernstein Department of Aerospace Engineering University of Michigan Ann Arbor MI Department of Mechanical and Aerospace Engineering Princeton University Princeton NJ

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This paper considers output-only identification for discrete-time hysteretic Lur'e (DTHL) systems, which are Lur'e systems with hysteretic feedback. The discrete-time model used to identify DTHL systems consists of asymptotically stable linear dynamics, a time delay, a washout filter, and a hysteretic nonlinear feedback mapping. A nonlinear least-squares identification algorithm is developed for DTHL systems as an extension of an existing technique for identifying Lur'e systems with memoryless nonlinearity feedback. Numerical examples are given to show the effectiveness of this technique for identifying DTHL systems.

关键词： Maximum likelihood detection Heuristic algorithms Delay effects Nonlinear filters filtering algorithms Numerical models

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UE-GS: High-Quality 3D Gaussian Splatting Real-Time Rendering for Unreal Engine

UE-GS: High-Quality 3D Gaussian Splatting Real-Time Renderin...

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Advanced algorithms and Control Engineering (ICAACE), International Conference on

作者： Xiaodan Jin Xuefei Han Hai Nan Zhijian Xue School of Computer Science and Engineering Chongqing University of Technology Chongqing China

ISBN: (数字)9798350361445

ISBN: (纸本)9798350361452

Recently, 3D Gaussian Splatting (3D-GS) has gained popularity in novel-view scene synthesis, achieving high fidelity and efficiency. However, the rendering quality of 3D-GS is still not up to the quality of the best methods in NeRF, and serious artifacts will occur when changing the sampling rate and changing the focal length or camera distance. Another significant problem is that interactive real-time rendering of complex scenes also has great limitations. To address this challenge, we have come up with a new rendering system, UE-GS, that blends 3D-GS with traditional rendering techniques in Unreal Engine 5 (UE5) to achieve higher quality visuals. Our approach draws inspiration from UE5's Level of Detail (LOD) technology. When changing the focal length or camera distance, we dynamically render LOD for different viewing levels, and replace the dilatation filter in 3D-GS with 2D EWA filtering, effectively alleviating the problems of aliasing and dilatation artifacts. Use octree to optimize spatial point data in complex scenes (40 million Gaussian +) and customize rendering components so that they are not limited by particle counts in UE5. We validated our approach on a variety of data sets and scenes that retain visual quality, achieving better rendering quality and faster training and reasoning speed than 3D-GS, while retaining the benefits of real-time performance. In addition, rendering in UE5 helps with scene editing in subsequent stages.

关键词： Training Visualization Three-dimensional displays Octrees filtering algorithms Rendering (computer graphics) Cameras

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An Adaptive Momentum Driven Variable Step-Size Filtered-X Weight Accumulated LMS for Improved HNANC

An Adaptive Momentum Driven Variable Step-Size Filtered-X We...

引用

IEEE International Smart Cities Conference (ISC2)

作者： Asutosh Kar Pradeep K. Shill Department of Electronics and Communication Engineering Dr B R Ambedkar National Institute of Technology Jalandhar Punjab

ISBN: (数字)9798350364316

ISBN: (纸本)9798350364323

In the scope of this paper, a group of adaptive algorithms with variable step size (VSS) is designed specifically for a hybrid narrow-band active noise control (HNANC) system. Traditional least mean squares (LMS) algorithms often face challenges in dynamic noise environments due to their fixed step size and slow convergence rates. To overcome these limitations, both the momentum variable step size filtered-x weight accumulated LMS algorithm and the VSS filtered-x LMS algorithm are presented as potential solutions to enhance precision and stability in an environment with numerous noise effects. The proposed approach utilizes VSS, which derives from the varying momentum factor of the variable. Additionally, it integrates these two factors to drive the weight accumulated least mean square technique for an HNANC system. The results of the simulation validate the enhancement in noise mitigation and its practical application, particularly in devices requiring high adaptability and performance, such as hearing aids and headphones that restrict background noise, which can be accomplished using the proposed algorithms in comparison to their existing alternatives.

关键词： Adaptive systems Smart cities Heuristic algorithms Noise Adaptive filters filtering algorithms Robustness Stability analysis Real-time systems Convergence

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Efficient Noise Cancellation in Lung Signals Using Pipelined Adaptive LMS Algorithm

Efficient Noise Cancellation in Lung Signals Using Pipelined...

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Smart Systems for Electrical, Electronics, Communication and Computer Engineering (ICSSEECC), International Conference on

作者： K. Sathesh T. Manivannan Kowsalya P E. Sathiyanarayanan P. Ramanathan E. Aravindraj Dept. of Electronics and Communication Engineering Madanapalle Institute of Technology & Science Madanapalle India

ISBN: (数字)9798350378177

ISBN: (纸本)9798350378184

The proposed work focuses on the use of the Pipelined Adaptive LMS algorithm as an effective noise cancellation technique in lung signals. The LMS algorithm is an adaptive filtering technique that has the capability to remove noise from signals by adjusting filter coefficients based on the input data. The study employs MATLAB and ModelSim-Altera as software tools to implement the algorithm. The outcomes showcase the efficacy of the Pipelined Adaptive LMS algorithm for canceling noise in lung signals. This research provides valuable insights into the application of adaptive filtering methods in medical applications, highlighting the potential of these techniques to improve the quality of medical signal processing. Additionally, the study emphasizes the importance of optimizing algorithm performance to ensure successful Application in real-world scenarios is crucial. This study contributes to the advancement of sophisticated noise cancellation techniques for medical applications and underscores the significance of adapting these techniques to improve patient care.

关键词： Software algorithms Signal processing algorithms Lung Medical services filtering algorithms Noise cancellation Mathematical models

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A Method for Designing the Perception Module of Autonomous Vehicles Using Stereo Depth and Semantic Segmentation

A Method for Designing the Perception Module of Autonomous V...

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International Conference on Control, Automation and Systems ( ICCAS)

作者： Fengchen Wei Weiji Wang Department of Engineering and Design University of Sussex Brighton UK

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

In this study, a perception module was developed for autonomous driving systems utilizing stereo matching and semantic segmentation models. This module serves two crucial functions for autonomous vehicles. Firstly, it combines object detection and stereo matching techniques to accurately determine distances for both the ego vehicle and target vehicles, thereby informing the control module's strategy selection. Secondly, it employs semantic segmentation models and filtering algorithms to devise a method for calculating drivable areas for autonomous vehicles, which is essential for the subsequent planning module. The modular design of the system allows for flexible training and selection of the backbone network for each module, enhancing adaptability and reducing computational costs during simultaneous training.

关键词： Training Automation Semantic segmentation Computational modeling Object detection filtering algorithms Control systems Planning Computational efficiency Autonomous vehicles

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Adaptive Spatial Modeling and Multi-Scale Attention Aggregation for Semantic Segmentation of Remote Sensing Images

Adaptive Spatial Modeling and Multi-Scale Attention Aggregat...

引用

Signal, Information and Data Processing (ICSIDP), IEEE International Conference on

作者： Wenying Yang Yuchuan Zhang Yuxuan Jin Yupei Wang Liang Chen National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing Institute of Technology Chongqing Innovation Center Chongqing China School of Artificial Intelligence Jianghan University Wuhan China National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing Institute of Technology Beijing China National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing Institute of Technology Chongqing Innovation Center Beijing Institute of Technology Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

As remote sensing technology advances and high-resolution sensors are deployed, the analysis of high-resolution remote sensing images encounters challenging issues, such as intra-class variability, and inter-class similarity, due to the unobvious appearance and complicated background. The high-resolution remote sensing images pose critical issues for precise semantic segmentation due to these fundamental issues. To this end, we propose an adaptive hierarchical aggregation network. Different from the previous approach of modeling semantic interdependencies solely within a single feature map in the channel dimension, we introduce multi-scale channel-wise feature aggregation to capture global contextual dependencies. Meanwhile, we design an adaptive detail-aware module to model long-range spatial dependencies, adaptively extracting effective details from different levels as compensation. Additionally, this module utilizes depth-wise separable convolution to selectively filter out irrelevant spatial details from lower-level feature maps. The outputs of the two modules are fused layer by layer to achieve refined feature representation, thereby generating precise pixel-level segmentation results. Our experiments are conducted on the Vaihingen dataset and the Potsdam dataset. The experimental results demonstrate that the proposed algorithm surpasses several existing state-of-the-art approaches.

关键词： Image sensors Adaptation models Adaptive systems Semantic segmentation Semantics filtering algorithms Feature extraction Data processing Sensors Remote sensing

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Optimal Design of (1+α)-order Bessel Filter and its Realization using DVCC

Optimal Design of (1+α)-order Bessel Filter and its Realiza...

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Global Conference for Advancement in Technology (GCAT)

作者： Shibendu Mahata Ritu Rani De Maity Dept. of Electrical Engineering Dr. B. C. Roy Engineering College Durgapur India

ISBN: (数字)9798350376685

ISBN: (纸本)9798350376692

This paper presents the optimal design of fractional-order Bessel filter of order (1+α), where, α ∈ (0, 1). The optimal values of the gain term and the coefficients of the pole polynomial are determined using two efficient metaheuristics, namely the marine predators algorithm (MPA) and the geometric mean optimizer (GMO). MATLAB simulations are carried out to evaluate the fractional-order Bessel filter functions for nine distinct values of α. Comparisons between MPA and GMO based designs regarding the fitness error, execution time, and algorithm convergence profile, are presented. Comparisons with the literature highlight improved modeling accuracy for the proposed approach. Implementation of the proposed MPA-based 1.5th order Bessel filter is carried out with the differential voltage current conveyor being used as the active circuit element.

关键词： Measurement Accuracy Metaheuristics Voltage filtering algorithms Active circuits Polynomials Integrated circuit modeling MATLAB Convergence

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The Interacting Multiple Model Algorithm Based on Anti-Divergent RBUKF

The Interacting Multiple Model Algorithm Based on Anti-Diver...

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Electrical Engineering and Automation (IFEEA), International Forum on

作者： Yuan Zhang Zhitong Zhong Shubo Liu Tao Li Dep. of Basic Sciences Dalian Naval Academy Dalian China Dep. of Missile & Shipboard Gunnery Dalian Naval Academy Dalian China

ISBN: (数字)9798331516611

ISBN: (纸本)9798331516628

Devoted to the problem of maneuvering target tracking under nonlinear observation, linear state and added noise, an interacting multiple model algorithm based on anti-divergent RBUKF (IMM-AD-RBUKF) is developed, which uses Rao-Blackwellised UKF (RBUKF) for filter and makes anti-divergent work. Simulation results show that this algorithm can improve the tracking precision and robustness of the multiple model algorithm at a low computation cost, and especially cope with the case of the model mismatching and the target's sudden maneuvering. It's a kind of engineering practical method suitable for high maneuvering target tracking.

关键词： Maximum likelihood detection Target tracking filtering Computational modeling Simulation Noise Nonlinear filters filtering algorithms Robustness Kalman filters

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