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2nd International Conference on Power, Control and Computing Technologies, ICPC2T 2022

作者： Gutte, Vitthal S Mundhe, Pramod Bhandari, Mahesh Dr. Vishwanath Karad MIT World Peace University School of Computer Engineering and Technology Pune India

ISBN: (纸本)9781665458580

In today's world, agriculture is the most important source of growth. It is an essential component of both economic and social life. Plant disease is becoming an important field in India, in the literal sense of the word. In the past, disease detection systems were designed for monocot or dicot plant families. Gradually, as scientific and special to some science or trade progress, more safe, good, ready, and working well methods are offered and have undergone growth for early detection of plant disease through the smallest wide space for turning time. We have instrumented a careful way to show monocot and dicot disease in this paper. Our methodical approach aids in the treatment of the disease by reducing the number of errors. To detect plant leaf disease, we took three steps. It primarily takes three forms: first, breaking down the leaf into parts, then removing the points, and finally, ordering. It has come to be part of the acted-on part of plant leaf using the k-means quince into group's expert way in the breaking down into parts process. The material's feel, appearance, and color are revealed after it is broken down into primarily form parts. Finally, the information gleaned from the features is applied to the order using the Support Guide Machine to detect plant disease. © 2022 IEEE.

关键词： Image color analysis Instruments Power control Clustering algorithms filtering algorithms Turning Information filters

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Multiple Object Tracking for Occluded Particles

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IEEE ACCESS 2021年 9卷 1524-1532页

作者： Qian, Yifei Ji, Ru Duan, Yuping Yang, Runhuai Anhui Med Univ Dept Biomed Engn Hefei 230022 Peoples R China

The precise detection and tracking of multiple particles under a microscope are of significance in the research of the individual and cluster behavior of dynamic bacteria and subcellular structures. However, the existing detection algorithms cannot separate occluded particles from each other, and most of the tracking algorithms aimed to address the occlusion involve several uncertainties. In this paper, a two-step detection algorithm based on the threshold segmentation and morphological open operation has been developed for identify non-fluorescent labeled particles under microscope, which could separate micro-contact targets. Moreover, we have proposed a novel correlation algorithm that can exploit the strengths of the global shortest path algorithm and Hungarian algorithm, which updating online in real time and considering the occlusion among particles. The proposed approach could achieve the temporal optimal match and spatial optimal solution by utilizing the multi-frame information. Moreover, the proposed method could realize the tracking of occluded particles tracking, and outperform the single global shortest path algorithm and Hungarian algorithm. The proposed method was successfully applied to six real image sequences with the maximum number of particles per frame ranging from 23 to 55, as well as a synthetic and fluorescent labeled sequence. The results of the contrast experiments demonstrated that the proposed algorithm is practical and can realize real-time tracking.

关键词： Target tracking filtering algorithms Detection algorithms Image edge detection Fluorescence Uncertainty Morphological operations Microscopic image multiple particles tracking target occlusion global data association

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An Improved AKAZE Algorithm for Feature Matching of Moving Objects 7

An Improved AKAZE Algorithm for Feature Matching of Moving O...

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7th International Conference on Cloud Computing and Big Data Analytics, ICCCBDA 2022

作者： Yongsheng, Lin Wenqiang, Fan Yuan, Zhao Peng, Liu School of Optoelectronic Information Yantai University Yantai China

ISBN: (纸本)9781665487115

Aiming at the problems of fast feature extraction and low matching accuracy of moving target detection features for moving targets in the existing image processing feature matching, an improved method is proposed based on the AKAZE algorithm. Using the nonlinear method of the AKAZE algorithm to construct the calculated feature points in the scale space, obtain the displacement of the same feature point between adjacent frames, and filter out the unsuitable feature points according to the rules of the improved algorithm. The experimental results show that although the improved algorithm has the disadvantage of increasing the matching time, by reducing the number of mismatched point pairs, the accuracy of feature matching can be improved relatively, and it is suitable for the capture of accurate objects in a small range. © 2022 IEEE.

关键词： Matched filters Fault tolerance Cloud computing Fault tolerant systems Object detection Streaming media filtering algorithms

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Fixed-Point Maximum Total Complex Correntropy Algorithm for Adaptive Filter

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2021年 69卷 2188-2202页

作者： Qian, Guobing Mei, Jiaojiao Iu, Herbert H. C. Wang, Shiyuan Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China Univ Western Australia Sch Elect Elect & Comp Engn Crawley WA 6009 Australia

Adaptive filtering for complex-valued data plays a key role in the field of signal processing. So far, there has been very little research for the adaptive filtering in complex-valued errors-in-variables (EIV) model. Compared with the complex correntropy, the total complex correntropy has shown superior performance in the EIV model. However, the current gradient based maximum total complex correntropy (MTCC) adaptive filtering algorithm has suffered from the tradeoff between fast convergence rate and low weight error power. In order to improve the performance of MTCC, we develop a fixed point maximum total complex correntropy (FP-MTCC) adaptive filtering algorithm in this study. The convergence analysis of the FP-MTCC is also provided in the paper. Furthermore, we develop two recursive FP-MTCC (RFP-MTCC) algorithms for the online adaptive filtering and provide the transient analysis of RFP-MTCC. Finally, the validity of the convergence and the superiority of the proposed algorithms are verified by simulations.

关键词： Convergence Adaptive filters Signal processing algorithms filtering Adaptation models Kernel filtering algorithms Complex domain errors-in-variables adaptive filtering fixed point

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Optimal Online Resonance Suppression in a Drive System Based on a Multifrequency Fast Search Algorithm

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IEEE ACCESS 2021年 9卷 55373-55387页

作者： Xia, Jiakuan Guo, Zhiyan Li, Zexing Shenyang Univ Technol Sch Elect Engn Shenyang 110870 Peoples R China

The resonant frequency drift caused by the change in mechanical parameters will cause the servo mechanism of CNC machine tools, robots and other equipment to produce mechanical resonance again. To address this problem, we propose a novel identification method of mechanical resonance based on the Fibonacci principle and a novel design method of notch filters based on optimization theory. First, by using a multifrequency sinusoidal signal, we design a fast search algorithm to search for the drift resonance frequency online;then, we optimize the notch filter to achieve fast and real-time resonance suppression by optimization theory. Compared with commonly employed passive resonance suppression methods, the proposed method can rapidly identify the parameters, more accurately suppress the resonance, minimize the phase angle loss and maintain the stability of the system. Finally, we apply the method to a 2-mass system experimental platform. The experimental results show that the proposed method is superior to the conventional passive resonant suppression method under the resonant frequency drift and other states and has strong robust performance.

关键词： Resonant frequency filtering algorithms Real-time systems filtering theory Servomotors Notch filters Optimization Servo mechanism mechanical resonance frequency drifts Fibonacci principle optimization theory notch filter phase angle loss

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Combinatorial Approach for the Access Points Map Correcting in the Mines Positioning Systems

Combinatorial Approach for the Access Points Map Correcting ...

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2022 International Russian Automation Conference, RusAutoCon 2022

作者： Larionov, Dmitry Voronov, Roman Inst.of Math and Information Technologies Petrozavodsk State University Petrozavodsk Russia

ISBN: (数字)9781665466554

ISBN: (纸本)9781665466554

Due to human factor localization systems in underground mines may be incorrectly installed. Positions of access points may be measured incorrectly. One of the most common errors is mixed access points: several access points replace each other. As a result, localization system output may be inaccurate. This article proposes an algorithm for resolving mixed access points positions problem. While the most obvious solution, brute-force search, is execution time-consuming, the proposed algorithm allows to significantly reduce this time by applying brute-force search to smaller set of access points chosen by observations of mobile object tracked by the localization system. To evaluate the proposed solution and compare the algorithm to brute-force search, several experiments with |synthetic data were conducted. The experimental results show the execution time advantage of the proposed algorithm over common brute-force search. © 2022 IEEE.

关键词： Location awareness Automation Human factors Position measurement filtering algorithms Search problems Trajectory

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$\mathcal{l}_{1}$ filtering for Positive Takagi–Sugeno Fuzzy Systems via Successive Linear Programming

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IEEE Transactions on Fuzzy Systems 2022年第6期31卷 1795-1805页

作者： Yingying Ren Da-Wei Ding Xiangpeng Xie School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Shunde Innovation School University of Science and Technology Beijing Foshan China Key Laboratory of Knowledge Automation for Industrial Processes Ministry of Education Beijing China Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing China

This article studies the $\mathcal{l}_{1}$ filtering problem for positive Takagi–Sugeno fuzzy systems. A pair of filters is sought to assure the stability and positivity of filtering error systems with guaranteed $\mathcal{l}_{1}$ performance indices. For this purpose, a pair of linear copositive Lyapunov functions that capture the positivity characteristics of filtering error systems is adopted to derive sufficient conditions for the existence of filters, which boils down to the bilinear programming problem. To solve this dilemma, we propose a convex approximation strategy, and thus, a sequence of convex surrogates is developed to reasonably replace the nonconvex constraints, based on which a successive linear programming algorithm is constructed. Therefore, the filters can be achieved by solving a battery of linear programming. Finally, the efficiency of the designed filtering scheme is justified by simulation validations.

关键词： filtering Nonlinear filters Maximum likelihood detection Linear programming filtering algorithms Programming Lyapunov methods

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A Two-layer Sketch for Entropy Estimation in Data Plane 7

A Two-layer Sketch for Entropy Estimation in Data Plane

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7th International Conference on Cloud Computing and Big Data Analytics, ICCCBDA 2022

作者： Lu, Jie Zhang, Zhen Chen, Hongchang PLA Information Engineering University Zhengzhou China Purple Mountain Laboratories Nanjing China National Digital Switching System Engineering Technological RD Center Zhengzhou China

ISBN: (纸本)9781665487115

Entropy-based approaches have been shown to aid a wide variety of network measurement applications such as load balancing, anomaly detection, traffic classification. Existing entropy estimation methods require frequent interaction between forwarding and control planes which increases the burden on the network and causes unnecessary delay. In this paper, we present Filter-Sketch, a two-layer sketch that supports frequency estimation with small and static memory allocation. Based on Filter-Sketch, we propose a new generation of mechanisms to calculate entropy at a line rate which completely executes in programmable data plane. The trace-driven evaluation shows that Filter-Sketch achieves higher accuracy than the existing data plane algorithm in entropy estimation where the relative error decreases 0.65 in average. © 2022 IEEE.

关键词： filtering Estimation filtering algorithms Load management Entropy Frequency estimation Computer networks

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GaMRed-Adaptive filtering of High-Throughput Biological Data

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2020年第1期17卷 149-157页

作者： Marczyk, Michal Jaksik, Roman Polanski, Andrzej Polanska, Joanna Yale Sch Med Dept Internal Med New Haven CT 06510 USA Silesian Tech Univ Data Min Div PL-44100 Gliwice Poland Silesian Tech Univ Syst Engn Grp PL-44100 Gliwice Poland Silesian Tech Univ Inst Informat PL-44100 Gliwice Poland

Data filtering based on removing non-informative features, with unchanged signal between compared experimental conditions, can significantly increase sensitivity of methods used to detect differentially expressed genes or other molecular components measured in high-throughput biological experiments. Criteria for data filtering can be stated on the basis of averages or variances of signal levels across samples. The crucial parts of feature filtering are selection of filter type and cut-off threshold, which are specific to the particular dataset. In this paper, we present an algorithm and a stand-alone application, GaMRed, for adaptive filtering insignificant features in high-throughput data, based on Gaussian mixture decomposition. We have tested the performance of our algorithm using datasets from three different high-throughput biological experiments. We estimated the number of differentially expressed features after applying multiple testing correction and performed functional analysis of obtained features using Gene Ontology terms. Also, we checked if the control of false discovery rate and family-wise error rate after applying feature filtering remains at appropriate level. GaMRed is fast, automatic, and does not require expert knowledge in parameter tuning. The algorithm increases sensitivity of methods used to find differentially expressed features and biological validity of the findings. The program can be downloaded from: http://***/***/pl/oprogramowanie-zaed.

关键词： filtering algorithms Biology Extraterrestrial measurements Throughput Sensitivity Information filtering Information filtering Gaussian mixture decomposition high throughput biological data

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Kalman Filter Based on Multiple Scaled Multivariate Skew Normal Variance Mean Mixture Distributions With Application to Target Tracking

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2021年第2期68卷 802-806页

作者： Lu, Chunguang Zhang, Yongshun Ge, Qichao Air Force Engn Univ Missile Def Coll Xian 710051 Peoples R China

In this brief, we first propose a multiple scaled multivariate skew normal variance-mean mixture (MSMSNVMM) distribution to model heavy-tailed and/or skew measurement noises (HTSMN) whose each dimension has different tail and skewness behaviors. The MSMSNVMM distribution has more flexible tail behaviors and richer skewness features than Gaussian scale mixture (GScM) distribution, generalized Gaussian scale mixture (GGScM) distribution and scale mixtures of skew normal (SMSN) distribution. Furthermore, we derive a robust Kalman filter based on variational Bayesian (VB) method. The superiority of the new filter is demonstrated in a maneuvering target tracking example.

关键词： filtering algorithms Mathematical model Kalman filters Robustness Gaussian distribution Adaptation models Multiple scaled multivariate skew normal variance-mean mixture distribution heavy-tailed and or skew noise variational Bayesian

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