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检索条件"主题词=Filtering algorithms"

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A novel algorithm for the restoration of AFM/STM images

A novel algorithm for the restoration of AFM/STM images

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International Symposium on Speech, Image Processing and Neural Networks

作者： Tian-Hu Yu S.K. Mitra Department of Information Engineering Chinese University of Hong Kong New Territories Hong Kong China Department of Electrical and Computer Engineering University of California Santa Barbara CA USA

ISBN: (纸本)078031865X

Images generated from the scanning tunneling microscope (STM) or atomic force microscope (AFM) imaging system can show microstructures of samples. However, resulting AFM/STM images are sometimes corrupted by streaks. Thus, to suppress such streaks becomes an important task in the processing of AFM/STM images. We analyze the generation of streaks, introduce a degradation model of the corrupted AFM/STM image, and then propose an adaptive notch filtering algorithm to remove the streaks. Some simulation results support the analysis and indicate the performance of the proposed algorithm.< >

关键词： Image restoration Atomic force microscopy Algorithm design and analysis Image generation Tunneling Microstructure Image analysis Degradation filtering algorithms Analytical models

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A method of vehicle trajectory restoration based on Kalman Filter

A method of vehicle trajectory restoration based on Kalman F...

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IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS)

作者： Jiaming Sun Xu Sun Zhonghan Zhan Jiaxu Zhou School of Mathematics Jilin University Changchun China College of Geoexploration Science and Technology Jilin University Changchun China

ISBN: (纸本)9781665456579

We propose a method for vehicle trajectory restoration in the field of intelligent transportation. We have a large number of data from Internet of Vehicle (IoV), including all information of vehicle status at every moment. First, we preprocess the data from IoV, perform data reduction and filter out the data that meets the requirements, and then build a Kalman filter trajectory model for noise removal. We conducted numerical experiments on the actual data from IoV and found that it is closer to the actual road, which eliminates the problem of GPS data deviation.

关键词： Navigation Roads Vehicle driving Transportation filtering algorithms Trajectory Numerical models

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Modeling and Performance Evaluation of Generative adversarial network for image denoising

Modeling and Performance Evaluation of Generative adversaria...

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International Conference on Computational Techniques, Electronics and Mechanical Systems (CTEMS)

作者： V NUTHNA Kavita Chachadi Leah S Joshi Department of Electrical and Electronics KLE Technological University Hubballi Karnataka

ISBN: (纸本)9781538677100

During transmission and reception the images are degraded by noise. Also Images captured using different low quality devices adversely affect the visual quality of images. The presence of the noise results in loss of visibility, gives a mottled, grainy, textured, or snowy appearance. Thus making the image visually unpleasing which drastically affects the human vision. In addition during image processing, presence of noise makes it hard for further processing (impulse, Gaussian white, salt and pepper, adversarial etc.,). Existing methods use conventional filters and Neural network models for image denoising where they compromise with the visibility of image after rigorous iterations of denoising algorithms. In this paper we implement CGANs for image denoising and evaluate the performance of CGAN with different Neural network models viz., CNN ,GAN for single or multiple image denoising problem. The qualitative performance of de-noised image/images is measured using PSNR and confusion matrix.

关键词： Gallium nitride Generators Generative adversarial networks Data models Neural networks filtering algorithms Noise reduction

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VCKSCF: Efficient Verifiable Conjunctive Keyword Search Based on Cuckoo Filter for Cloud Storage

VCKSCF: Efficient Verifiable Conjunctive Keyword Search Base...

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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Chan Fan Xiaolei Dong Zhenfu Cao Jiachen Shen Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China Cyberspace Security Research Center Peng Cheng Laboratory Shenzhen and Shanghai Institute of Intelligent Science and Technology Tongji University China

ISBN: (数字)9781665403924

ISBN: (纸本)9781665403931

Searchable Symmetric Encryption(SSE) remains to be one of the hot topics in the field of cloud storage technology. However, malicious servers may return incorrect search results intentionally, which will bring significant security risks to users. Therefore, verifiable searchable encryption emerged. In the meantime, single-keyword query limits the applications of searchable encryption. Accordingly, more expressive searchable encryption schemes are desirable. In this paper, we propose a verifiable conjunctive keyword search scheme based on Cuckoo filter (VCKSCF), which significantly reduces verification and storage overhead. Security analysis indicates that the proposed scheme achieves security in the face of indistinguishability under chosen keyword attack and the unforgeability of proofs and search tokens. Meanwhile, the experimental evaluation demonstrates that it achieves preferable performance in real-world settings.

关键词： Cloud computing Privacy Keyword search filtering algorithms Information filters Encryption Servers

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A survey on various image enhancement techniques for underwater acoustic images

A survey on various image enhancement techniques for underwa...

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International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT)

作者： K. Sharumathi R. Priyadharsini Department of Computer Science and Engineering SSN College of Engineering Chennai India

ISBN: (纸本)9781467399401

Image enhancement techniques serve as a preprocessing step in segmentation, object detection and recognition in computer vision applications. These techniques may not be suitable for enhancing the acoustic images as the scene of the sea-floor is captured by using special instruments such as Sonar which uses sound as a source to capture image. The acoustic images contain speckle noise which is caused by the interference of the sea-floor sediment and multi-path reverberation. This paper presents a survey on various image enhancement techniques applied on acoustic images. It is recently proved that transformation techniques such as wavelet, curvelet and contourlet are more suitable for removing speckle noises in acoustic images. This paper also provides a framework for understanding the way by which different types of noises in an acoustic image can be removed by filtering techniques.

关键词： Acoustics Sonar Image enhancement Wavelet transforms filtering filtering algorithms

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Distributed Information Fusion Particle Filter

Distributed Information Fusion Particle Filter

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International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC

作者： Lin Mao Da Wei Yang College of Electromechanical and Information Engineering Dalian Nationalities University Dalian China

ISBN: (纸本)9781479949540

The method of particle filters as a main solution for non-linear is widely used in digital communication, target tracking, automatic control and signal processing region. In order to eliminate the existing problems such as low precision and low stability, the information fusion is introduced to fuse multiple different sensor measurement information according to a certain fusion criterions. This schematic increases not only the measurement information deterministic and stability, but also the precision and reliability of the particle filter without adding any measurement base stations. The paper proposes an information fusion particle filter algorithm that takes the local particle filter results into distribution fusion utilizing the three weighted information fusion criterions including matrix, scalar and vector (diagonal matrix) methods based on linear minimum variance. Then, a three-sensor bearings-only passive location example illustrates the effectiveness of this proposed algorithm.

关键词： Particle filters Information filters Sensor fusion filtering algorithms Atmospheric measurements

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An Event Detection Approach Based on Improved CUSUM Algorithm and Kalman Filter

An Event Detection Approach Based on Improved CUSUM Algorith...

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IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Kaijie Fang Yixuan Huang Qifeng Huang Shihai Yang Zhixin Li Hanmiao Cheng Sate Grid JiangSu Electric Power Co. Ltd. Marketing Service Center Nanjing China

ISBN: (数字)9781728196060

ISBN: (纸本)9781728196077

Non-intrusive load monitoring (NILM) is an intelligent perception technology of electricity consumption information on the consumer side. Event detection, the fundamental and indispensable step of the NILM framework, has a direct impact on the accuracy of the results of load decomposition. This paper presents a novel NILM event detection approach based on Kalman filter and improved cumulative sum (CUSUM) algorithm. Firstly, this paper use Kalman filter to handle acquired data for sliding windows to make the power curve more smooth and suitable for next event detection step. An adaptive factor is introduced in the traditional CUSUM algorithm to improve the detection accuracy. The experiment results show that the proposed approach can not only effectively detect various input and cutoff events with different power level but also suits for the detection of the long transient events.

关键词： Event detection System integration filtering algorithms Information filters Kalman filters Transient analysis Testing

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A new variable step-size zero-point attracting projection algorithm

A new variable step-size zero-point attracting projection al...

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Asilomar Conference on Signals, Systems & Computers

作者： Jianming Liu Steven L Grant Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla Missouri

ISBN: (纸本)9781479923915

This paper proposes a new variable step-size (VSS) scheme for the recently introduced zero-point attracting projection (ZAP) algorithm. The proposed variable step-size ZAPs are based on the gradient of the estimated filter coefficients' sparseness that is approximated by the difference between the sparseness measure of current filter coefficients and an averaged sparseness measure. Simulation results demonstrate that the proposed approach provides both faster convergence rate and better tracking ability than previous ones.

关键词： Least squares approximations Adaptive filters Dispersion Current measurement Convergence Signal processing algorithms filtering algorithms

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Stability and performance tradeoff with discrete time triangular search minimum seeking

Stability and performance tradeoff with discrete time triang...

引用

American Control Conference (ACC)

作者： Y. Zhang Numerical Technologies Inc. San Jose CA USA

In this paper, we consider a framework and a discrete time algorithm based on triangular search for a general class of minimum seeking problems. Stability of the algorithm is analyzed that provides a sufficient condition for stability and convergence of the algorithm assuming a deterministic system, and illustrates the trade-offs between stability and performance with various design parameters.

关键词： Stability analysis Algorithm design and analysis filtering algorithms Control systems Information filtering Information filters Smoothing methods Low pass filters Drives Performance analysis

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Box-particle CPHD filter for multi-target tracking

Box-particle CPHD filter for multi-target tracking

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International Conference on Control, Automation and Information Sciences (ICCAIS)

作者： Meng Liang Liping Song Hongbing Ji Yufei Wang Department of Electronic Engineering Xidian University Xi'an China

ISBN: (纸本)9781479998937

A novel approach called box-particle cardinalized probability hypothesis density (BP-CPHD) filter for multi-target tracking is proposed in this paper. A box particle is a random sample that occupies a small and controllable rectangular region of nonzero volume in the target state space. Box-particle filter is capable of dealing with three sources of uncertainty: stochastic, set-theoretic and data association uncertainty. Furthermore, it decreases the number of particles significantly and reduces the runtime considerably. The proposed algorithm based on box-particle is able to reach a similar accuracy to a SMC-CPHD filter with much less computational costs. Not only does it propagate the PHD, but also propagates the cardinality distribution of target number. Therefore, it generates more accurate and stable instantaneous estimates of the target number and admits more false alarm processes than the box-particle probability hypothesis density (BP-PHD) filter does. The effectiveness and reliability of the proposed algorithm are verified by the simulation results.

关键词： filtering theory Target tracking Clutter Atmospheric measurements Particle measurements Approximation methods filtering algorithms

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