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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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Fractional Order Modeling and Internal Model Control of Dielectric Elastomer Actuator 13

Fractional Order Modeling and Internal Model Control of Diel...

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13th Asian Control Conference, ASCC 2022

作者： Xu, Zhichao Wu, Jundong Wang, Yawu China University of Geosciences School of Automation Wuhan China

ISBN: (纸本)9788993215236

To achieve the tracking control objective of the dielectric elastomer actuator (DEA), this paper proposes the fractional order modeling method and the fractional order internal model control method. Firstly, a fractional order transfer function (FOTF) model of the DEA is built to depict its complex "memory"property. Then, to achieve the computer control, an integer order approximation model (IOAM) of the FOTF model is built by using the Oustaloup filter. Considering that the order of the IOAM is too high, a reduced integer order approximation model is established by using the Ramer-Douglas-Peucker line simplification algorithm to facilitate the system controller design. Next, a fractional order internal model controller (FOIMC) is designed, and a reduced integer order approximation controller of the FOIMC is developed. Finally, some experiments are exerted to demonstrate the effectiveness of the proposed control method. © 2022 ACA.

关键词： Digital control Computational modeling Random access memory Transfer functions filtering algorithms Dielectric elastomers Approximation algorithms

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Combination of Elman Neural Network and Kalman Network for Modeling of Batch Distillation Process 13

Combination of Elman Neural Network and Kalman Network for M...

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13th Asian Control Conference, ASCC 2022

作者： Putri, Adi Novitarini Machbub, Carmadi Idris Hidayat, Egi Muhammad Institut Teknologi Bandung School of Electrical Engineering and Informatics 40132 Indonesia

ISBN: (纸本)9788993215236

Batch distillation is one of the nonlinear systems in a real-world application. Before designing and implementing a control system, a model is needed to capture its dynamics. The batch distillation process could be represented in a state-space model. Nonetheless, the sensor is limited so it could not access its states directly from the sensor. Then, the state estimation method is needed to estimate its state trajectories. On the other hand, state estimation is one of the fundamental problems in signal processing. Kalman Filter (KF) is an optimal filtering algorithm and the most widely used in signal processing. Meanwhile, deep learning is the most active and present topic nowadays on modeling and estimation. We use a recurrent neural network scheme to develop the Nonlinear State Space (NLSS) model. In this research, we use KalmanNet to overcome the state estimation problem if the noise statistic matrices are unknown. This idea has been done using a Long Short-Term Memory (LSTM) scheme which produces the Kalman Gain value. In this study, we compare conventional Kalman gain value and KalmanNet to find which one is better to solve the state estimation problem. From the experiment, the combination of the Elman Neural Network (ENN) model and KalmanNet which have the best performance from its Mean-Squared Error (MSE) value, 1.30E03. © 2022 ACA.

关键词： Recurrent neural networks Distillation equipment Signal processing filtering algorithms Control systems Trajectory State-space methods

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Improved Rabin-Karp Algorithm Using Bloom Filter 27

Improved Rabin-Karp Algorithm Using Bloom Filter

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27th International Computer Conference, Computer Society of Iran, CSICC 2022

作者： Moeini, Masoumeh Shahhoseini, Hadi Shahriar Iran University Of Science And Technology School Of Electrical Engineering Tehran Iran

ISBN: (纸本)9781665480277

String matching algorithms are used widely in computer science that is a very important issue in text processing. Also, string matching algorithms are used as basic components in the practical software in operating systems. A lot of research is performed in this field that hash based matching algorithms like Rabin-Karp is one of their fastest, but due to the rapid growth of data volumes, traditional algorithms are not sufficient. To solve this problem, combining Bloom filter features with string matching algorithms, makes it possible to reduce the execution time. In present paper, a modified version of the Rabin-Karp algorithm is presented by using a Bloom filter as preprocessing phase that can early detect pattern absence. In addition, this approach maximize speed up and reduce the number of patterns needed for the exact Rabin-Karp matching phase. Accordingly, the proposed results as well as the Rabin-Karp implementations have been compared to verify the impact of the proposed method. © 2022 IEEE.

关键词： Hash functions Matched filters Runtime Operating systems Software algorithms filtering algorithms Software

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Minimax Design of Graph Filter Using Chebyshev Polynomial Approximation

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2021年第5期68卷 1630-1634页

作者： Tseng, Chien-Cheng Lee, Su-Ling Natl Kaohsiung Univ Sci & Technol Dept Comp & Commun Engn Kaohsiung 824005 Taiwan Chang Jung Christian Univ Dept Comp Sci & Informat Engn Tainan 711301 Taiwan

In this brief, the minimax design problem of graph filter using Chebyshev polynomial approximation (CPA) is studied. First, conventional CPA graph filter design is investigated to show that it does not provide the minimax design, so the peak error of the spectral response of the designed filter is not minimized. Then, a spectral transformation is used to convert the minimax design problem of CPA graph filter into the one of the type-I linear-phase FIR digital filter such that the Parks-McClellan method can be employed to obtain the optimal filter coefficients of minimax design. Next, using the recurrence relation of Chebyshev polynomials, an implementation structure of CPA graph filter with low computational complexity is presented. Finally, a graph signal denoising application example is illustrated to show the usefulness of the proposed CPA graph filter.

关键词： Finite impulse response filters IIR filters Optimized production technology filtering algorithms Filter banks Chebyshev approximation Circuits and systems Chebyshev polynomial digital filter graph filter minimax design signal denoising

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LCL Filter based Grid-tied Converter with Single Current Sensor Approach 2

LCL Filter based Grid-tied Converter with Single Current Sen...

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

作者： Kumari, Khushboo Jain, Amit Kumar Indian Institute of Technology Delhi Department of Electrical Engineering New Delhi India

ISBN: (纸本)9781665458580

This work is dedicated to implementing a LCL filter-based grid-tied converter with a reduced sensor approach. A conventional system requires two grid-side current sensors, two capacitor-side voltage sensors, and two inverter-side current sensors. This paper has proposed a novel method that leads to a substantial reduction of the sensor. In this method, a single grid-side current sensor is required to perform the control methodology. In this technique, the grid current reference in the d-q axis is used for estimation of grid current in ß axis. As an outcome, the size, weight, cost, and complexity of the system are reduced. A comparative assessment is performed between the proposed system and the conventional system. The system offers a cost-efficient solution for grid integration. The proposed system is validated by simulation results obtained from Matlab/Simulink platform. © 2022 IEEE.

关键词： Costs Simulation Estimation Prototypes filtering algorithms Inverters Power system reliability

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