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Monitoring of power system dynamics under incomplete PMU observability condition

IET GENERATION TRANSMISSION & DISTRIBUTION 2021年第9期15卷 1435-1450页

作者： Ortiz, Gabriel Rehtanz, Christian Colome, Graciela TU Dortmund Univ Fac Elect Engn & Informat Technol Inst Energy Syst Energy Efficiency & Energy Econ Emil Figge Str 70 D-44227 Dortmund Germany Natl Univ San Juan CONICET Inst Elect Energy IEE Fac Engn Ave Libertador Gen San Martin Oeste 1109 RA-J5407 San Juan Argentina

This work presents a hybrid state estimation procedure that allows power system dynamics associated to slow and fast transient events to be accurately monitored considering a limited amount of phasor measurement units. The proposal represents an enhanced version of a previously developed static state estimation approach. This time, two main changes are introduced. First, a weighted least absolute value estimator instead the conventional weighted least square technique is used to estimate bus voltages in transient regime. This makes the estimation process more robust at fast scan rates. Second, an extended Kalman filter based dynamic state estimator is integrated. Thus, the proposed scheme is able to estimate, along with static variables, dynamic variables of all generators and motors in the power system regardless of the availability of phasor measurement unit measurements at terminal buses. This is possible thanks to a novel data-mining based methodology for full phasor measurement unit observability restoration. Performance parameters such as accuracy, computing time and convergence properties are assessed by applying the estimation procedure to the New England benchmark system under different operating conditions.

关键词： filtering methods in signal processing Other topics in statistics Interpolation and function approximation (numerical analysis) Power system measurement and metering

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An improved algorithm using weighted guided coefficient and union self-adaptive image enhancement for single image haze removal

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IET IMAGE processing 2021年第11期15卷 2680-2692页

作者： Zhou, Guangbin He, Lifeng Qi, Yong Yang, Meimei Zhao, Xiao Chao, Yuyan Shaanxi Univ Sci & Technol Sch Elect Informat & Artificial Intelligence Xian 710021 Peoples R China Aichi Prefectural Univ Fac Informat Sci & Technol Nagakute Aichi Japan Xian Univ Posts & Telecommun Sch Elect Engn Xian Peoples R China Nagoya Sangyo Univ Fac Current Business Nagoya Aichi Japan

The visibility of outdoor images is usually significantly degraded by haze. Existing dehazing algorithms, such as dark channel prior (DCP) and colour attenuation prior (CAP), have made great progress and are highly effective. However, they all suffer from the problems of dark distortion and detailed information loss. This paper proposes an improved algorithm for single-image haze removal based on dark channel prior with weighted guided coefficient and union self-adaptive image enhancement. First, a weighted guided coefficient method with sampling based on guided image filtering is proposed to refine the transmission map efficiently. Second, the k-means clustering method is adopted to calibrate the original image into bright and non-bright colour areas and form a transmission constraint matrix. The constraint matrix is then marked by connected-component labelling, and small bright regions are eliminated to form an atmospheric light constraint matrix, which can suppress the halo effect and optimize the atmospheric light. Finally, an adaptive linear contrast enhancement algorithm with a union score is proposed to optimize restored images. Experimental results demonstrate that the proposed algorithm can overcome the problems of image distortion and detailed information loss and is more efficient than conventional dehazing algorithms.

关键词： Optical, image and video signal processing filtering methods in signal processing Computer vision and image processing techniques

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Multi-sensor particle filtering with multi-step randomly delayed measurements

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IET SCIENCE MEASUREMENT & TECHNOLOGY 2021年第1期15卷 35-43页

作者： Chen, Yunqi Yan, Zhibin Harbin Inst Technol Ctr Control Theory & Guidance Technol Harbin Peoples R China Harbin Inst Technol Sch Sci Shenzhen 518055 Peoples R China

This paper develops particle filtering for multi-sensor systems with randomly delayed measurements, where the general case that random delay can be multi-step rather than one-step or two-step is considered. Moreover, different sensors can have different delay steps and delay probabilities. Random delays are assumed to be mutually independent for different sensors and modelled by a separate sequence of random variables obeying discrete distributions. Since random delay leads to the actual measurements being dependent rather than independent given states, and this dependence becomes more complicated with the increase of random delay step, a new formula of the local likelihood density is proposed and then a new weighting scheme is adopted in particle filtering to deal with these difficulties. The proposed method is applied to two examples to testify its effectiveness and superiority.

关键词： filtering methods in signal processing signal processing theory Sensor fusion Other topics in statistics Other topics in statistics

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Design of cooperative matched filter for detection of chemical agents

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ELECTRONICS LETTERS 2021年第5期57卷 216-218页

作者： Yu, Hyeong-Geun Lee, Chang Sik Park, Dong-Jo Chang, Dong Eui Nam, Hyunwoo Korea Adv Inst Sci & Technol Sch Elect Engn Daejeon South Korea Agcy Def Dev CRB Def Technol Directorate Daejeon South Korea

A matched filter (MF) is one of the most widely used detectors for the detection of chemical agent (CA) clouds in the passive hyperspectral imaging system. To improve the detection performance of the MF, a linear cooperation scheme that allocates cooperation coefficients to the spectra of the neighbouring pixels is proposed. The optimal cooperation coefficients, which removes noise signatures whilst minimising the distortion of CA signatures, are acquired by finding the maximum likelihood estimator of the cooperation coefficients. It is proved that a moving average scheme that assigns the same coefficients is the optimal cooperation scheme. Finally, a cooperative MF with the optimal cooperation scheme is designed. It is demonstrated that the proposed cooperative MF is capable of robust detection performance via outdoor experiments with actual CA data measured by a Bruker HI-90 instrument.

关键词： Optical, image and video signal processing filtering methods in signal processing Computer vision and image processing techniques Other topics in statistics Other topics in statistics

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On the steady-state performance of bias-compensated LMS algorithm

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ELECTRONICS LETTERS 2021年第2期57卷 85-88页

作者： Pimenta, Rodrigo Resende, Leonardo Petraglia, Mariane R. Haddad, Diego B. CEFET RJ Rio De Janeiro Brazil IFRJ Rio De Janeiro Brazil Univ Fed Rio de Janeiro Rio de Janeiro Brazil

Adaptive filtering algorithms are widespread today owing to their flexibility and simplicity. Due to environments in which they are normally immersed, their robustness against noise has been a topic of interest. Traditionally, in the literature it is assumed that noise is mainly active in the reference signal. Since this hypothesis is often violated in practice, recently some papers have advanced strategies to compensate the bias introduced by noisy excitation data. The contributions of this paper are twofold. The first one establishes that, in some conditions, the bias-compensated least mean square algorithm implements an optimum estimator, in the sense that it presents the smallest variance of the set of unbiased estimators. Since the asymptotic mean-square performance of this algorithm has not yet been investigated in detail, the second contribution adopts an energy conservation relationship to derive its theoretical steady-state mean squared distortion. The final result is presented in a closed form, is consistent with simulations and is able to provide important guidelines to the designer.

关键词： filtering methods in signal processing signal processing theory Interpolation and function approximation (numerical analysis) Interpolation and function approximation (numerical analysis)

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A non-uniform NSAF-SF adaptive algorithm

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ELECTRONICS LETTERS 2021年第1期57卷 38-41页

作者： Xavier, P. P. S. Petraglia, M. R. Haddad, D. B. INPI Rio De Janeiro Brazil Univ Fed Rio de Janeiro Rio de Janeiro Brazil CEFET RJ Comp Engn Dept BR-25620003 Rio De Janeiro Brazil

Speech enhancement and acoustic noise reduction are two important tasks where adaptive filtering algorithms emerge as a competitive solution. Unfortunately, in such applications the convergence rate of the system identification is hampered when the excitation data is highly correlated. Subband adaptive algorithms have been developed to address such issue. A recently proposed low-complexity subband adaptive structure with sparse subfilters is generalised, in order to permit a non-uniform filter bank structure. This generalisation brings additional flexibility to the resulting critically decimated adaptive structure, which allows one to adapt it to the idiosyncrasies of the application of interest without losing the perfect-reconstruction property. A closed-form solution for the optimal values that the adaptive coefficient should assume in order to accurately emulate a given impulse response is derived. Simulations reveal that the resulting algorithm may outperform recently published subband adaptive filtering algorithms, thereby requiring even less computational effort.

关键词： Speech and audio signal processing filtering methods in signal processing Speech processing techniques

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YOU MAY ENTER: Automated ID checks face scrutiny

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Engineering and Technology 2021年第6期16卷 26-27页

作者： Courtney, Martin

This article discusses the use of a contactless AI-driven facial-recognition system being used for ID checks and queue management at the Tokyo Olympics 2020. This will be used for staff, volunteers, athletes and media who have already given their consent, not the general public. The system is based on NEC NeoFace Watch technology, and uses generalised matching face detection method, along with an artificial neural network model called the generalised learning vector quantisation algorithm, to search and select facial features for facial matching. The perturbation space method then coverts the two-dimensional images into three dimensions, allowing rotation of the candidates head. Further processing with illumination filters and adaptive regional blend matching method, minimises the impact of local changes such as hats etc. providing a better photograph match against a central database image. An IC chip embedded security lanyard pass, containing personal ID and authentication details will also be used. Data privacy concerns are discussed, especially due to the current use of NEC technology in criminal surveillance applications, with the Tokyo 2020 organisation responding with a promise to comply with local privacy law. Possibilities of using the technology to enhance Covid-19 security and aid in contact-tracing for the event is also discussed.

关键词： facial matching local privacy law data privacy artificial neural network model image matching management generalised matching face detection method contactless AI-driven facial-recognition system Image recognition neural nets Spatial and pictorial databases Administration of other service industries visual databases Tokyo Olympics 2020 head rotation epidemics authentication details generalised learning vector quantisation algorithm IC chip embedded security lanyard pass personal ID vector quantisation illumination filters two-dimensional images queue management face recognition feature selection three dimensional images criminal surveillance applications central database image perturbation space method Data security Codes Computer vision and image processing techniques filtering methods in signal processing sport stereo image processing image filtering NEC NeoFace Watch technology facial feature selection contact-tracing adaptive regional blend matching method ID checks learning (artificial intelligence) Covid-19 security

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A novel video noise reduction method based on PDE, adaptive grouping, and thresholding techniques

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JOURNAL OF ENGINEERING-JOE 2021年第10期2021卷 605-620页

作者： Yahya, Ali Abdullah Tan, Jieqing Hu, Min Anqing Normal Univ Sch Comp & Informat Anqing 246011 Peoples R China Hefei Univ Technol Sch Comp & Informat Hefei Peoples R China

Undoubtedly, video block-matching and 3D filtering (VBM3D) has achieved a significant improvement in video denoising. Nevertheless, in practice, failure to distinguish between the different noise areas, ignoring noise variances and pixel intensity, false-similar patches, and poor matching are the challenges faced by the VBM3D filter. To avoid these drawbacks, a new video denoising algorithm is proposed. This algorithm based on the nature of the noise areas and the spatial distance between the reference block and its candidate blocks. In the algorithm, hard-thresholding in VBM3D is replaced by adaptive filtering. In this adaptive filter, soft-thresholding is applied to the heavily contaminated areas, whereas anisotropic diffusion filter is applied to the slight-noise areas. Applying adaptive filtering creates a balance between noise removal and edges conservation. To avert the occurrence of the poor choice of the threshold, noise variances, clean image coefficients, and pixel intensity are taken into consideration during computing the proposed adaptive threshold. Due to the strong possibility of similar correlative blocks happening in the vicinity, an adaptive grouping technique is proposed to compute the distance between a reference block and its candidate blocks. Applying this technique helps to reduce the occurrence of false-similar blocks and poor matching.

关键词： 3D filtering Computer vision and image processing techniques candidate blocks adaptive filters slight-noise areas adaptive filtering noise removal edges conservation heavily contaminated areas adaptive threshold similar correlative blocks Optical, image and video signal processing different noise areas image matching adaptive filter video block-matching video noise reduction method adaptive grouping technique false-similar patches noise variances filtering methods in signal processing VBM3D filter pixel intensity Video signal processing soft-thresholding video denoising algorithm thresholding techniques false-similar blocks video signal processing Integral transforms Interpolation and function approximation (numerical analysis) Image recognition poor matching reference block anisotropic diffusion filter hard-thresholding filtering theory image denoising Other topics in statistics

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Fast image interpolation using the bilateral filter

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IET IMAGE processing 2012年第7期6卷 877-890页

作者： Hung, K. -W. Siu, W. -C. Hong Kong Polytech Univ Dept Elect & Informat Engn Ctr Signal Proc Hong Kong Hong Kong Peoples R China

In this study, the authors propose a new image interpolation technique using the bilateral filter to estimate the unknown high-resolution pixels. Compared with the least-squares estimation, a small-kernel bilateral filter has the advantages of fast computation and stability. The range distance of the bilateral filter is estimated using a novel maximum a posterior estimation, in order to consider both the diagonal and vertical-horizontal correlations. For the consideration of global consistency, the pixel-based soft-decision estimation (SAI) is proposed to constrain the consistency of edge statistic within a local window. Experimental results show that the interpolated images using the proposed algorithm give an average of 0.462, 0.413, 0.532 and 0.036 dB peak signal-to-noise ratio (PSNR) improvement compared with that using the bicubic interpolation, linear minimum mean squares error estimation, new edge-directed interpolation (NEDI) and SAI respectively. The subjective quality agrees with the PSNR as well. More importantly, the proposed algorithm is fast and it requires around 1/60 computational cost of the SAI.

关键词： image resolution pixel-based soft-decision estimation edge statistic high-resolution pixels vertical-horizontal correlation filtering methods in signal processing diagonal correlation global consistency least square estimation Computer vision and image processing techniques Other topics in statistics range distance PSNR improvement Optical, image and video signal processing bicubic interpolation maximum likelihood estimation signal-to-noise ratio linear minimum mean square error estimation fast image interpolation local window new edge-directed interpolation Interpolation and function approximation (numerical analysis) filtering theory interpolation maximum a posterior estimation NEDI small-kernel bilateral filter SAI least mean squares methods

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Perturbation-enhanced feature correlation filter for robust iris recognition

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IET BIOMETRICS 2012年第1期1卷 37-45页

作者： Zhang, M. Sun, Z. Tan, T. Chinese Acad Sci Ctr Biometr & Secur Res Inst Automat Natl Lab Pattern Recognit Beijing 100190 Peoples R China

Visual pattern of human iris provides rich texture information for personal identification. However, it is challenging to match intra-class iris images with large variations in applications. This study proposes a perturbation-enhanced feature correlation filter (PFCF) for robust iris matching. PFCF is developed based on quad-phase minimum average correlation energy filter, but it has two significant improvements. First, PFCF is performed on Gabor filtered iris images to encode both local and global features. On the one hand, Gabor images can enhance the local details of iris texture. On the other hand, correlation filters describe the regional appearance information and measure the global similarity between iris images efficiently. Secondly, artificially perturbed iris images are generated to model intra-class variations. Also, a set of additional correlation filters are developed accordingly as the gallery templates. The decision is determined by the fusion result of multiple correlation filters. Therefore PFCF not only takes the advantages of Gabor images and correlation filters but also enlarges the amount of enrolled templates for robust iris matching. Extensive experiments on three challenging iris image databases demonstrate that the proposed method outperforms the state-of-the-art methods according to its robustness against deformation, rotation, occlusion, blurring and illumination changes in iris images.

关键词： robust iris recognition intraclass iris image matching quadphase minimum average correlation energy filter image matching Image recognition global features personal identification human iris intraclass variations image fusion artificially perturbed iris images perturbation-enhanced feature correlation filter global similarity measures regional appearance information local features Gabor filtered iris images feature extraction image enhancement correlation methods Computer vision and image processing techniques filtering methods in signal processing image texture multiple correlation filters Gabor filters iris image database visual pattern PFCF iris recognition texture information

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