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检索条件"主题词=Filtering algorithms"

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Design and Resource Allocation of NOMA-based Transmission Scheme for Industrial Collaborative AR

Design and Resource Allocation of NOMA-based Transmission Sc...

引用

IEEE Globecom Workshops

作者： Farnaz Khodakhah Aamir Mahmood Sarder Fakhrul Abedin Kyi Thar Patrik Österberg Mikael Gidlund Department of Information Systems & Technology Mid Sweden University Sundsvall Sweden

ISBN: (纸本)9781665459761

Collaborative augmented reality (AR), which enables interaction and consistency in multi-user AR scenarios, is a promising technology for AR-guided remote monitoring, optimization, and troubleshooting of complex manufacturing processes. However, for uplink high data rate demands in collaborative-AR, the design of an efficient transmission and resource allocation scheme is demanding in resource-constrained wireless systems. To address this challenge, we propose a collaborative non-orthogonal multiple access (C-NOMA)-enabled transmission scheme by exploiting the fact that multi-user interaction often leads to common and individual views of the scenario (e.g., the region of interest). C-NOMA is designed as a two-step transmission scheme by treating these views separately and allowing users to offload the common views partially. Further, we define an optimization problem to jointly optimize the time and power allocation for AR users, with an objective of minimizing the maximum rate-distortion of the individual views for all users while guaranteeing a target distortion of their common view for its mutual significance. For its inherent non-linearity and non-convexity, we solve the defined problem using a primal-dual interior-point algorithm with a filter line search as well as by developing a successive convex approximation (SCA) method. The simulation results demonstrate that the optimized C-NOMA outperforms the non-collaborative baseline scheme by 23.94% and 77.28% in terms of energy consumption and achievable distortion on the common information, respectively.

关键词： Wireless communication Simulation Collaboration filtering algorithms Distortion Information filters Search problems

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A METHOD FOR BAND REGISTRATION OF SMALL MOVING TARGET BASED ON STARING IMAGING SPECTROMETER

A METHOD FOR BAND REGISTRATION OF SMALL MOVING TARGET BASED ...

引用

Workshop on Hyperspectral Image and Signal Processing

作者： Hao Ding Huijie Zhao Precision Opto-mechatronics Technology Key Laboratory of Education Ministry Beihang University Beijing China

Thus far, capturing a moving target's spectral is still a very challenging task. Some researches have been performed on this problem, but many of them are still far from practicability. The motive of this paper is to propose a method for band registration of small moving target based on traditional staring imaging spectrometers. Viewing spectral misregistration as targets moving in a special image sequence which is composed of images corresponding to several different bands, targets' spectral will be gathered if they can be detected and associated. The edge-TDLMS filter is employed to detect targets in different-band images, and MHT algorithm is used to realize data association. At last, targets' spectral can be formed by the image intensities in the corresponding positions originated from their own tracks. Computer simulations were conducted to evaluate the effectiveness of the method.

关键词： Target tracking Wiener filters Hyperspectral imaging filtering algorithms Imaging Image edge detection

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Speech recognition with localized time-frequency pattern detectors

Speech recognition with localized time-frequency pattern det...

引用

IEEE Workshop on Automatic Speech Recognition and Understanding

作者： Ken Schutte James Glass MIT Computer Science and Artificial Intelligence Laboratory Cambridge MA USA

ISBN: (纸本)9781424417452

A method for acoustic modeling of speech is presented which is based on learning and detecting the occurrence of localized time-frequency patterns in a spectrogram. A boosting algorithm is applied to both build classifiers and perform feature selection from a large set of features derived by filtering spectrograms. Initial experiments are performed to discriminate digits in the Aurora database. The system succeeds in learning sequences of localized time-frequency patterns which are highly interpretable from an acoustic-phonetic viewpoint. While the work and the results are preliminary, they suggest that pursuing these techniques further could lead to new approaches to acoustic modeling for ASR which are more noise robust and offer better encoding of temporal dynamics than typical features such as frame-based cepstra.

关键词： Speech recognition Time frequency analysis Acoustic signal detection Spectrogram Detectors Boosting filtering algorithms Spatial databases Automatic speech recognition Acoustic noise

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Hierarchical Estimation of Vehicle Key Parameters Using KF-RLS Method

Hierarchical Estimation of Vehicle Key Parameters Using KF-R...

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2024 8th International Conference on Electrical, Mechanical and Computer Engineering (ICEMCE)

作者： Ao Chi Juan Wei Tongming Wei Guanyu Song Liangchun Qin Min Wei Yong Gao Liping Lu Intelligent Transportation Systems Research Center Wuhan University of Technology Wuhang Hubei China Technical Center SAIC GM Automobile Co Ltd Liuzhou Guangxi China School of Automotive Engineering Wuhan University of Technology Wuhang Hubei China School of Computer and Artificial Intelligence Wuhan University of Technology Wuhang Hubei China

ISBN: (数字)9798331506230

ISBN: (纸本)9798331506247

In order to achieve accurate estimation of critical vehicle and road parameters that cannot be directly measured, without the addition of extra sensors, this paper proposes a joint parameter estimation algorithm combining Kalman filtering and Recursive Least Squares (KF-RLS). In this study, Kalman filtering (KF) is employed to reduce the state noise detected by sensors, while Recursive Least Squares (RLS) utilizes the filtered state data in conjunction with the longitudinal dynamics model of the vehicle for parameter estimation. After the design of the algorithm, a hierarchical estimation strategy was adopted; this strategy first estimates the mass of vehicle, subsequently determines the position of the center of gravity, and finally identifies the tire-road friction coefficient based on these estimates. Simulation experiments conducted in the TruckSim environment demonstrate that the proposed KF-RLS joint estimation algorithm exhibits superior performance in terms of accuracy and anti-interference capability compared to the single RLS method.

关键词： Parameter estimation Accuracy Heuristic algorithms Friction Noise Estimation filtering algorithms Sensors Kalman filters Vehicle dynamics

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Performance of Multiplierless FIR Filter based on CSD and Binary: A Comparative Study

Performance of Multiplierless FIR Filter based on CSD and Bi...

引用

International Conference on Signal Processing and Communication (ICSC)

作者： N. Sajwan A. Kumar I. Sharma L. K. Balyan Indian Institute of Information Technology Design and Manufacturing Jabalpur India

In this paper, a comparative study of binary and CSD representation forms on filter coefficients has been presented for acute justification of their selection for designing multiplierless finite impulse response (FIR) filter. For this purpose, a well-known computationally efficient nature-inspired cuckoo search optimization algorithm (CSA) is exploited for optimization perspective. An objective function is constructed to minimize the mean square error of designed filter to its ideal response, and it has been observed that the least number of adders and signed power of two terms (SPTs) are acquired when CSD representation is used.

关键词： Finite impulse response filters filtering algorithms Adders IIR filters Optimization Band-pass filters

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Visual tracking based on compressive sensing and particle filter

Visual tracking based on compressive sensing and particle fi...

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Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： Wenhui Huang Jason Gu Xin Ma School of Control Science and Engineering Shandong University Jinan Shandong China Department of Electrical and Computer Engineering Dalhousie University Halifax Nova Scotia Canada

ISBN: (纸本)9781479958306

A robust appearance model is usually required in visual tracking, which can handle pose variation, illumination variation, occlusion and many other interferences occurring in video. So far, a number of tracking algorithms make use of image samples in previous frames to update appearance models. There are many limitations of that approach: 1) At the beginning of tracking, there exists no sufficient amount of data for online update because these adaptive models are data-dependent and 2) in many challenging situations, robustly updating the appearance models is difficult, which often results in drift problems. In this paper, we proposed a tracking algorithm based on compressive sensing theory and particle filter framework. Features are extracted by random projection with data-independent basis. Particle filter is employed to make a more accurate estimation of the target location and make much of the updated classifier. The robustness and the effectiveness of our tracker have been demonstrated in several experiments.

关键词： Target tracking Particle filters Classification algorithms Feature extraction Sparse matrices filtering algorithms

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Target Tracking Based on Collaborative Learning Kernelized Correlation Filter

Target Tracking Based on Collaborative Learning Kernelized C...

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International Symposium in Sensing and Instrumentation in IoT Era (ISSI)

作者： Bin Sun Chaofeng Li Liling Zeng Qingbing Sang School of Internet of Things Engineering Jiangnan University Wuxi China Institute of Logistics Science and Engineering Shanghai Maritime University Shanghai China

ISBN: (纸本)9781538656396

In this paper, a tracking algorithm based on collaborative learning Kernelized Correlation Filter is proposed. According to the framework of KCF, two trackers based on HoG and CN are cooperatively trained, and independent scale adaptive algorithm is used at the same time, and we call it collaborative learning Kernelized Correlation Filter (CL-KCF) algorithm. Our experimental results show that the proposed algorithm has higher tracking accuracy and robustness than other trackers, and can automatically adapt to the target's scale change.

关键词： Target tracking filtering algorithms Correlation Detectors Collaborative work Training Feature extraction

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Kalman Filter State Transformation Application in INS/GNSS Integrated Navigation for Polar Navigation

Kalman Filter State Transformation Application in INS/GNSS I...

引用

International Conference on Information Fusion

作者： Honggang Guo Zhikun Liao Zhonghong Liang Pengcheng Mu Jie Yuan Lin Wang College of Advanced Interdisciplinary Studies National University of Defense Technology Changsha China Nanhu Laser Laboratory National University of Defense Technology Changsha China

ISBN: (数字)9781737749769

ISBN: (纸本)9798350371420

Kalman filter is an important technology to realize information fusion between Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS). One of the most important variables in the Kalman filter structure is the state variable, which is the basis of maintaining system stability. However, due to the inherent singularity in polar regions, the INS/GNSS integrated navigation system will not work properly in polar regions. Different coordinate systems are often used in trans-polar navigation to solve the problems in the polar regions, therefore the Kalman filter state variable transformation is inevitable in the process of entering or leaving the polar regions, which will bring instability and even failure to the system. Here, this paper proposes a Kalman filter state transformation algorithm for INS/GNSS polar integrated navigation based on Psi-angle error model to ensure the numerical stability of the Kalman filter during its state transformation. Key to this success is to establish the transformation relationship between different filter state variables as well as their covariance matrices in different navigation coordinate systems, then the state variables and the covariance matrices are transformed simultaneously. After presenting the state variable transformation algorithm and the system description, a numerical evaluation is carried out to assess the presented algorithm with regard to stability and accuracy.

关键词： Global navigation satellite system Navigation Switches filtering algorithms Transversal filters Stability analysis Numerical models Kalman filters Covariance matrices Numerical stability

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Research on Image Matching Method Based on ORB and Grid Motion Statistics

Research on Image Matching Method Based on ORB and Grid Moti...

引用

Chinese Control and Decision Conference, CCDC

作者： Mujun Xie Yuxin Ye Changhong Jiang Chuansong Liu Yanran Cao School of Electrical and Electronic Engineering Changchun University of Technology Changchun

ISBN: (纸本)9781665478977

The ORB algorithm has a small amount of calculation and can quickly abstract numerous feature points. The grid motion statistics algorithm can filter the initial match, reduce false matches, and retain more inliers. Combining ORB and grid motion statistics algorithm to complete the indoor matching of two adjacent frames of pictures. Proved by experiment: The algorithm used in this paper can eliminate mismatched point pairs and retain more inliers. Compared with the ORB+RANSAC algorithm, the inliers ratio is increased by 7.62% on average. The algorithm in this paper can be applied to the indoor positioning of vision-based mobile robots and has strong robustness in the feature point matching of image rotation and scaling.

关键词： Matched filters Image matching filtering algorithms Robustness Mobile robots

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Active control of fluid-bome noise in hydraulic systems using in-series and by-pass structures

Active control of fluid-bome noise in hydraulic systems usin...

引用

UKACC International Conference on Control (CONTROL)

作者： Min Pan Andrew Hillis Nigel Johnston Department of Mechanical Engineering University of Bath Bath United Kingdom

The nature of digital hydraulic systems may cause severe fluid-borne noise problems because of the pulsed nature of the flow. An effective method to reduce the noise that does not impair the system performance and efficiency is needed. This article reports on initial investigations of an active valve for pressure pulsation attenuation in switched inertance hydraulic systems (SIHS) based on in-series and by-pass structures. The in-series structure represents a valve arranged in line between the SIHS and the load providing a controlled pulsating pressure drop, whilst for the by-pass structure the valve was arranged in parallel with the load providing a controlled pulsating bleed-off flow. A high-performance piezoelectric valve was used as the active controller. Adaptive notch filters with the filtered-X least mean square algorithm were applied for pressure pulsation attenuation, while a frequency-domain least mean square filter was used for secondary path identification. Simulated and experimental results show that excellent cancellation was achieved using the proposed methods, which have several advantages over passive noise control systems. Comparison of the in-series and by-pass structures is discussed in terms of system performance, robustness and advantages. The proposed control structures are very promising for fluid-borne noise cancellation in fluid power systems or other fluid systems with severe noise or vibration problems.

关键词： Valves Noise Power harmonic filters Harmonic analysis Switches Adaptive filters filtering algorithms

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