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2021 International Conference on Automatics and Energy, ICAE 2021

作者： Akishin, A.D. Nikolaev, A.P. Pisareva, A.V. Bauman Moscow State Technical University National Technical University Building 1 5 Vtoraya Baumanskaya Str. Moscow105005 Russia The Department of Medical and Technical Management Bauman Moscow State Technical University National Technical University Building 1 5 Vtoraya Baumanskaya Str. Moscow105005 Russia

Monitoring such health parameters as cardiac rate (CR), respiration rate (RR), blood pressure (BP), degree of oxygen in blood (SpO2), body temperature and other requires careful approach to design and development of medical devices. New non-invasive methods introduced in measuring human physiological parameters based on photoplethysmography (PPG) demonstrated their significant potential in monitoring the state of an organism, but their use in wearable devices is largely hampered by exposure to motion artifacts. This article presents a device for photoplethysmographic studies using various adaptive algorithms for processing the registered signals. The work uses artificial intelligence technologies to monitor the heart rate exposed to external mechanical and electrical interference worsening accuracy characteristics of the system. Besides, system architecture was developed, and a device model was manufactured, which made it possible to measure the optimal algorithm for digital signal processing. When using the PPG system, methods of adaptive signal processing based on Wiener filters, filters on the method of least squares (MLS) and Kalman filtering were used. To ensure heart rate monitoring with the given accuracy, studies were performed with participation of volunteers, and analysis was carried out of the results of various signal processing algorithms operation. In the course of experimental studies, a method was proposed to estimate the heart rate calculation accuracy and to analyze the external noise filtering efficiency by adaptive algorithms. PPG designed and developed system made it possible to monitor the heart rate with the given accuracy, control the organism current state and could be used as a means of cardiovascular disease diagnostics. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： adaptive algorithms

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A Sigmoid Least Mean Fourth based Control Scheme for a Single-Stage Grid-Tied PV System

A Sigmoid Least Mean Fourth based Control Scheme for a Singl...

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2021 International Symposium of Asian Control Association on Intelligent Robotics and Industrial Automation, IRIA 2021

作者： Parida, Abhisek Subudhi, Bidyadhar Ray, Pravat Kumar Institute of Technology Nirma University Ahmedabad382481 India Indian Institute of Technology School of Electrical Sciences Goa Ponda403401 India National Institute of Technology Department of Electrical Engineering Rourkela769008 India

ISBN: (纸本)9781665433235

In a single-stage grid-tied PV system, the Voltage Source Inverter (VSI) performs the task of MPPT along with delivery of high quality power to the grid. However, the presence of non-linear loads gives rise to Power Quality (PQ) issues in the distribution network. Therefore, it is necessary to develop a suitable control scheme for efficient functioning of the VSI. In this work, a Sigmoid Least Mean Fourth (SLMF) based control technique is discussed for a single-stage grid-tied PV system. The sigmoidal based adaptive algorithms embeds the conventional cost function into the sigmoidal framework to obtain improved performance by exploiting the saturation characteristics of the non-linear sigmoid function. The performance of the proposed SLMF based control scheme is simulated in MATLAB/Simulink under dynamic changes in load and environmental conditions and is compared with its conventional counterpart in terms of oscillation in weights and Total Harmonic Distortion (THD) of grid current. © 2021 IEEE.

关键词： adaptive algorithms

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Explicit a posteriori error representation for variational problems and application to TV-minimization

arXiv

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arXiv 2023年

作者： Bartels, Sören Kaltenbach, Alex Department of Applied Mathematics University of Freiburg Hermann–Herder–Straße 10 Freiburg79104 Germany Institute of Mathematics Technical University of Berlin Straße des 17. Juni 136 Berlin10623 Germany

In this paper, we propose a general approach for explicit a posteriori error representation for convex minimization problems using basic convex duality relations. Exploiting discrete orthogonality relations in the space of element-wise constant vector fields as well as a discrete integration-by-parts formula between the Crouzeix–Raviart and the Raviart–Thomas element, all convex duality relations are transferred to a discrete level, making the explicit a posteriori error representation –initially based on continuous arguments only– practicable from a numerical point of view. In addition, we provide a generalized Marini formula for the primal solution that determines a discrete primal solution in terms of a given discrete dual solution. We benchmark all these concepts via the Rudin–Osher–Fatemi model. This leads to an adaptive algorithm that yields a (quasi-optimal) linear convergence *** Codes 35Q68, 49M25, 49M29, 65N30, 65N50 Copyright © 2023, The Authors. All rights reserved.

关键词： adaptive algorithms

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An adaptive knowledge distillation algorithm for text classification

An adaptive knowledge distillation algorithm for text classi...

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2021 IEEE International Conference on Emergency Science and Information Technology, ICESIT 2021

作者： Chen, Zuqin Hu, Tingkai Chen, Chao Ge, Jike Wu, Chengzhi Cheng, Wenjun School of Intelligent Technology and Engineering Chongqing University of Science and Technology Chongqing401331 China

ISBN: (纸本)9781665435314

Using knowledge distillation to compress pre-trained models such as Bert has proven to be highly effective in text classification tasks. However, the overhead of tuning parameters manually still hinders their application in practice. To alleviate the cost of manual tuning of parameters in training tasks, inspired by the inverse decrease of the word frequency of TF-IDF, this paper proposes an adaptive knowledge distillation method (AKD). This core idea of the method is based on the Cosine similarity score which is calculated by the probabilistic outputs similarity measurement in two networks. The higher the score, the closer the student model's understanding of knowledge is to the teacher model, and the lower the degree of imitation of the teacher model. On the contrary, we need to increase the degree to which the student model imitates the teacher model. Interestingly, this method can improve distillation model quality. Experimental results show that the proposed method significantly improves the precision, recall and F1 value of text classification tasks. However, training speed of AKD is slightly slower than baseline models. This study provides new insights into knowledge distillation. © 2021 IEEE.

关键词： adaptive algorithms

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Fractional-order LMS filter Based on Chaotic Particle Swarm 3

Fractional-order LMS filter Based on Chaotic Particle Swarm

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3rd International Academic Exchange Conference on Science and Technology Innovation, IAECST 2021

作者： Wan, Honglin Sheng, Hu Yang, Jingxin Dalian Jiaotong University School of Computer and Communication Engineering Dalian China

ISBN: (纸本)9781665402675

In the traditional LMS adaptive algorithm, not only is the step factor a fixed value, but there is also an irreconcilable conflict between the convergence speed and the steady-state error. Although fractional-order LMS algorithms have been proposed to improve the convergence characteristics, the step factor is still a fixed value, which is prone to divergence when not set properly. In this paper, the fractional-order LMS algorithm is improved and combined with the chaotic particle swarm algorithm. The fractional-order LMS algorithm is combined with a chaotic particle swarm algorithm, and the fixed step factor value in the fractional-order LMS algorithm is changed to a dynamically varying step factor. The results show that the convergence speed and steady-state error of the fractional-order LMS filter are effectively improved by adding the chaotic particle swarm. © 2021 IEEE.

关键词： adaptive algorithms

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Speed sensorless control of permanent magnet synchronous motor based on robust adaptive algorithm 3

Speed sensorless control of permanent magnet synchronous mot...

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2020 3rd International Symposium on Power Electronics and Control Engineering, ISPECE 2020

作者： Wang, Zeng Hui Zhang, Jun Hong Zhang, Yin Heng Xiao, Huan Yu Zhang, Xiao Chen College of Electrical Engineering Naval University of Engineering Wuhan City Hubei Province430000 China Radar Sergeant School Air Force Early Warning Academy Wuhan City Hubei Province430000 China

In order to solve the problem that the parameters of the regulator and the actual parameters do not match due to the time-varying motor parameters in the operation of PMSM, this paper adopts a robust adaptive control strategy based on linear matrix inequality (LMI) based on the model reference adaptive method (MRAS) to consider the uncertainties of the motor parameters in the state equation of the motor control system, the controller parameters are obtained by solving the LMI. The simulation model of PMSM speed sensorless control system is built in Simulink. The simulation results show that the system can track the given speed well and has strong robustness when the motor parameters change. © Published under licence by IOP Publishing Ltd.

关键词： adaptive algorithms

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Parallel Feedback Active Noise Control of MRI acoustic noise with Signal Decomposition using hybrid RLS-NLMS adaptive algorithms

Parallel Feedback Active Noise Control of MRI acoustic noise...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Anshuman Ganguly Sri Hari Krishna Vemuri Issa Panahi Department of Electrical Engineering The University of Texas Dallas TX USA University of Texas at Dallas Richardson TX US

This paper presents a cost-effective adaptive feedback Active Noise Control (FANC) method for controlling functional Magnetic Resonance Imaging (fMRI) acoustic noise by decomposing it into dominant periodic components and residual random components. Periodicity of fMRI acoustic noise is exploited by using linear prediction (LP) filtering to achieve signal decomposition. A hybrid combination of adaptive filters-Recursive Least Squares (RLS) and Normalized Least Mean Squares (NLMS) are then used to effectively control each component separately. Performance of the proposed FANC system is analyzed and Noise attenuation levels (NAL) up to 32.27dB obtained by simulation are presented which confirm the effectiveness of the proposed FANC method.

关键词： Noise Acoustic noise adaptive filters Attenuation Magnetic resonance imaging Convergence adaptive algorithms

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Local Lipschitz Filters for Bounded-Range Functions with Applications to Arbitrary Real-Valued Functions

arXiv

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arXiv 2023年

作者： Lange, Jane Linder, Ephraim Raskhodnikova, Sofya Vasilyan, Arsen MIT United States Boston University Department of Computer Science United States

We study local filters for the Lipschitz property of real-valued functions f: V → [0, r], where the Lipschitz property is defined with respect to an arbitrary undirected graph G = (V, E). We give nearly optimal local Lipschitz filters both with respect to 1-distance and 0-distance. Previous work only considered unbounded-range functions over [n]d. Jha and Raskhodnikova (SICOMP ‘13) gave an algorithm for such functions with lookup complexity exponential in d, which Awasthi et al. (ACM Trans. Comput. Theory) showed was necessary in this setting. We demonstrate that important applications of local Lipschitz filters can be accomplished with filters for functions whose range is bounded in [0, r]. For functions f: [n]d → [0, r], we achieve running time (dr log n)O(log r) for the 1-respecting filter and dO(r) polylog n for the 0-respecting filter, thus circumventing the lower bound. Our local filters provide a novel Lipschitz extension that can be implemented locally. Furthermore, we show that our algorithms are nearly optimal in terms of the dependence on r for the domain {0, 1}d, an important special case of the domain [n]d. In addition, our lower bound resolves an open question of Awasthi et al., removing one of the conditions necessary for their lower bound for general range. We prove our lower bound via a reduction from distribution-free Lipschitz testing and a new technique for proving hardness for adaptive algorithms. Finally, we provide two applications of our local filters to real-valued functions, with no restrictions on the range. In the first application, we use them in conjunction with the Laplace mechanism for differential privacy and noisy binary search to provide mechanisms for privately releasing outputs of black-box functions, even in the presence of malicious clients. In particular, our differentially private mechanism for arbitrary real-valued functions runs in time 2polylogmin(r,nd) and, for honest clients, has accuracy comparable to the Laplace mechan

关键词： adaptive algorithms

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Research and Implementation of FPGA-based Local adaptive Thresholding

Research and Implementation of FPGA-based Local Adaptive Thr...

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Machine Vision, Image Processing and Imaging Technology (MVIPIT), International Conference on

作者： Wangchun Zhu Chang Hu School of Electronic Engineering and Automation Guilin University of Electronic Science and Technology Guilin China

ISBN: (数字)9798350306545

ISBN: (纸本)9798350306552

In view of the problems of the current fixed threshold algorithm, which is prone to clustering effect caused by uneven distribution of ambient light, unable to distinguish the foreground and background of the image, and unable to extract a large number of feature points, this paper adopts the innovative design of accelerating algorithm processing of verilog HDL hardware circuit platform. The innovation of the algorithm lies in using the average value of local extreme points and the texture feature of the whole image to adapt to the changes of complex environment in real time. The experimental results show that after the image is processed by the local adaptive image algorithm, the feature point information of the target contour can still be well extracted when the image is interfered by the uneven distribution of light. The similarity fitting of the feature point of the contour can reach 86%, which is improved compared with the fixed threshold of 73%. There are no obvious breakpoints, voids, white noise and other problems, and a relatively complete image is displayed. At the same time, the image target can be easily recognized when the background and foreground colors are switched.

关键词： Thresholding (Imaging) Fitting Clustering algorithms adaptive algorithms Logic gates White noise Feature extraction

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Quantifying Privacy Vulnerability to Socialbot Attacks: An adaptive Non-Submodular Model

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IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING 2020年第3期8卷 855-868页

作者： Li, Xiang Smith, J. David Pan, Tianyi Dinh, Thang N. Thai, My Univ Florida Dept Comp & Informat Sci & Engn Gainesville FL 32611 USA Virginia Commonwealth Univ Dept Comp Sci Richmond VA 23284 USA

Privacy breaches are one of the biggest concerns on Online Social Networks (OSNs), especially with an introduction of automated attacks by socialbots, which can automatically extract victims' private content by exploiting social behavior to befriend them. The key insight of this attack is that by intelligently sending friend requests to a small subset of users, called the Critical Friending Set (CFS), such a bot can evade current defense mechanisms. We study the vulnerability of OSNs to socialbot attacks. Specifically, we introduce a new optimization problem, Min-Friending, which identifies a minimum CFS to friend in order to obtain at least Q benefit, which quantifies the amount of private information the bot obtains. The two main challenges of this problem are how to cope with incomplete knowledge of network topology and how to model users' responses to friend requests. In this paper, we show that Min-Friending is inapproximable within a factor of (1 - o(1) lnQ and present an adaptive approximation algorithm using adaptive stochastic optimization. The key feature of our solution lies in the adaptive method, where partial network topology is revealed after each successful friend request. Thus the decision of whom to send a friend request to next is made with the outcomes of past decisions taken into account. Traditional tools break down when attempting to place a bound on the performance of this technique with realistic user models. Therefore, we additionally introduce a novel curvature-based technique to construct an approximation ratio of lnQ for a model of user behavior learned from empirical measurements on Facebook.

关键词： SocialBots attacks social networks analysis content-centric privacy adaptive algorithms non-submodularity

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