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fuzzy system Design Using Current Amplifier for 20 nm CMOS Technology

Computers, Materials & Continua 2022年第7期72卷 1815-1829页

作者： Shruti Jain Cherry Bhargava Vijayakumar Varadarajan Ketan Kotecha Jaypee University of Information Technology Waknaghat172234India Symbiosis Institute of Technology Symbiosis International(Deemed University)Pune411021India School of Computer Science and Engineering The University of New South WalesSydneyNSW 2052Australia Symbiosis Centre for Applied Artificial Intelligence Symbiosis International(Deemed University)Pune411021India

In the recent decade,different researchers have performed hardware implementation for different applications covering various areas of *** this research paper,a novel analog design and implementation of different steps of fuzzy systems with current differencing buffered amplifier(CDBA)are proposed with a compact structure that can be used in many signal processing *** proposed circuits are capable of wide input current range,simple structure,and are highly *** electrical parameters were compared for the proposed fuzzy system when using different membership *** novelty of this paper lies in the electronic implementation of different steps for realizing a fuzzy system using current *** the power supply voltage of CDBA is 2V,it results in 155mW,power dissipation;4.615KΩ,input resistance;366KΩ,output resistances;and 189.09 dB,common-mode rejection ratio.A 155.519 dB,voltage gain,and 0.76V/μs,the slew rate is analyzed when the power supply voltage of CDBAis *** fuzzy system is realized in 20nm CMOS technology and investigated with an output signal of high precision and high speed,illustrating that it is suitable for realtime *** this research paper,a consequence of feedback resistance on the adder circuit and the defuzzified circuit is also analyzed and the best results are obtained using 100K *** structure has a low hardware complexity leading to a low delay and a rather high quality.

关键词： Current amplifiers membership functions fuzzy system fuzzy operators defuzzified circuit feedback resistance

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Output Linearization of Single-Input Single-Output fuzzy system to Improve Accuracy and Performance

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Computers, Materials & Continua 2023年第5期75卷 2413-2427页

作者： Salah-ud-din Khokhar QinKe Peng Muhammad Yasir Noor Department of Automation Science and Technology(system Engineering Institute) School of Electronics and Information EngineeringXi’an Jiaotong UniversityXi’anShaanxi710049China Department of Computer Science G.C.UniversityLahore54000PunjabPakistan Department of Physics(Electronics) G.C.UniversityLahore54000PunjabPakistan

For fuzzy systems to be implemented effectively,the fuzzy membership function(MF)is essential.A fuzzy system(FS)that implements precise input and output MFs is presented to enhance the performance and accuracy of single-input single-output(SISO)FSs and introduce the most applicable input and output MFs protocol to linearize the fuzzy system’s *** a variety of non-linear techniques,a SISO FS is *** results of FS experiments conducted in comparable conditions are then *** simulated results and the results of the experimental setup agree fairly *** findings of the suggested model demonstrate that the relative error is abated to a sufficient range(≤±10%)and that the mean absolute percentage error(MPAE)is reduced by around 66.2%.The proposed strategy to reduceMAPE using an FS improves the system’s performance and control *** using the best input and output MFs protocol,the energy and financial efficiency of every SISO FS can be improved with very little tuning of *** proposed fuzzy system performed far better than other modern days approaches available in the literature.

关键词： Mean absolute percentage error membership functions relative error fuzzy system

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Optimal guaranteed cost control for an uncertain discrete T-S fuzzy system with time-delay

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控制理论与应用（英文版） 2009年第2期7卷 144-150页

作者： Renming WANG Thierry Marie GUERRA Juntao PAN College of Electrical Engineering and Information Technology Three Gorges University Yichang Hubei 443002 China LAMIH UMR CNRS Universite de Valenciennes et du Hainaut-Canbresis Le Mont Houy Valenciennes Cedex France Key Laboratory of Measurement and Control of CSE of Ministry of Education Southeast University Nanjing Jiangsu 210096 China

This paper considers the guaranteed cost control problem for a class of uncertain discrete T-S fuzzy systems with time delay and a given quadratic cost function. Sufficient conditions for the existence of such controllers are derived based on the linear matrix inequalities （LMI） approach by constructing a specific nonquadratic Lyapunov-Krasovskii functional and a nonlinear PDC-like control law. A convex optimization problem is also formulated to select the optimal guaranteed cost controller that minimizes the upper bound of the closed-loop cost function. Finally, numerical examples are presented to demonstrate the effectiveness of the proposed approaches.

关键词： fuzzy system Time delay Linear matrix inequalities (LMI) Guaranteed cost control

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Genetics Based Compact fuzzy system for Visual Sensor Network

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Computer systems Science & Engineering 2023年第4期45卷 409-426页

作者： Usama Abdur Rahman C.Jayakumar Deepak Dahiya C.R.Rene Robin Department of Computer Science and Engineering Jerusalem College of EngineeringChennaiTamil Nadu600100India Department of Computer Science and Engineering Sri Venkateswara College of EngineeringChennaiTamil Nadu602117India College of Computer and Information Sciences(CCIS) Majmaah UniversityMajmaah11952Kingdom of Saudi Arabia Department of Computer Science and Engineering Sri Sairam Engineering CollegeChennai600044India

As a component of Wireless Sensor Network(WSN),Visual-WSN(VWSN)utilizes cameras to obtain relevant data including visual recordings and static *** from the camera is sent to energy efficient sink to extract key-information out of *** applications range from health care monitoring to military *** a network with VWSN,there are multiple challenges to move high volume data from a source location to a target and the key challenges include energy,memory and I/O *** this case,Mobile Sinks(MS)can be employed for data collection which not only collects information from particular chosen nodes called Cluster Head(CH),it also collects data from nearby nodes as *** innovation of our work is to intelligently decide on a particular node as CH whose selection criteria would directly have an impact on QoS parameters of the ***,making an appropriate choice during CH selection is a daunting task as the dynamic and mobile nature of MSs has to be taken into *** propose Genetic Machine Learning based fuzzy system for clustering which has the potential to simulate human cognitive behavior to observe,learn and understand things from manual *** architecture is designed based on Mamdani’s fuzzy *** parameters are derived based on the model residual energy,node centrality,distance between the sink and current position,node centrality,node density,node history,and mobility of sink as input variables for decision making in CH *** inputs received have a direct impact on the fuzzy logic rules mechanism which in turn affects the accuracy of *** proposed work creates a mechanism to learn the fuzzy rules using Genetic Algorithm(GA)and to optimize the fuzzy rules base in order to eliminate irrelevant and repetitive *** algorithmbased machine learning optimizes the interpretability aspect of fuzzy *** results are obtained using *** result shows that the classification acc

关键词： Visual sensor network fuzzy system genetic based machine learning mobile sink efficient energy life of network

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Research on the Method of Nonlinear Combining Forecasts based on fuzzy system

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systems Science and systems Engineering 2000年第3期10卷 301-307页

作者： DONG Jing\|rong College of Management, Chongqing University, Chongqing 400044, China

In this paper, a new nonlinear combination forecasting method based on fuzzy system is presented to overcome some limitation in linear combination forecasting. Furthermore, the corresponding genetic learning algorithm is employed to identify the parameter of the fuzzy system model and partition of fuzzy subsets. Theoretical analysis and forecasting examples all show that the new technique has reinforcement learning properties and universalized capabilities. With respect to combined modeling and forecasting of non stationary time series in nonlinear systems, which has some uncertainties, the method is more accurate and reasonable than other existing combining methods which are based on linear combination of forecasts.

关键词： combination forecasting fuzzy system genetic algorithm

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An Automatic Threshold Selection Using ALO for Healthcare Duplicate Record Detection with Reciprocal Neuro-fuzzy Inference system

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Computers, Materials & Continua 2023年第3期74卷 5821-5836页

作者： Ala Saleh Alluhaidan Pushparaj Anitha Subbappa Ved Prakash Mishra P.V.Chandrika Anurika Vaish Sarthak Sengupta Department of Information systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhKSA.P.O.Box:8442811671 Department of Electronics and Communication Engineering National Institute of Technical Teacher Training and ResearchChandigarh160019India Department of Periodontology JSS Dental College&HospitalJSS Academy of Higher Education and ResearchMysuru570015India Department of Computer Science and Engineering Amity UniversityDubai345019United Arab Emirates Department of Management/Economics Prin LN Welingkar Institute of Management Development and ResearchMumbai400019India Department of Management Studies Indian Institute of Information TechnologyAllahabad211012India

Esystems based on EHRs(Electronic health records)have been in use for many years and their amplified realizations have been felt *** still have been pioneering collections of massive volumes of health *** detections involve discovering records referring to the same practical components,indicating tasks,which are generally dependent on several input parameters that experts *** linkage specifies the issue of finding identical records across various data *** similarity existing between two records is characterized based on domain-based similarity functions over different ***-duplication of one dataset or the linkage of multiple data sets has become a highly significant operation in the data processing stages of different data mining *** objective is to match all the records associated with the same *** measures have been in use for representing the quality and complexity about data linkage algorithms,and many other novel metrics have been *** outline of the problem existing in themeasurement of data linkage and de-duplication quality and complexity is *** article focuses on the reprocessing of health data that is horizontally divided among data custodians,with the purpose of custodians giving similar features to sets of *** first step in this technique is about an automatic selection of training examples with superior quality from the compared record pairs and the second step involves training the reciprocal neuro-fuzzy inference system(RANFIS)*** the Optimal Threshold classifier,it is presumed that there is information about the original match status for all compared record pairs(i.e.,Ant Lion Optimization),and therefore an optimal threshold can be computed based on the respective ***,Clinical Decision(CD),and Cork Open Research Archive(CORA)data repository help analyze the proposed method with evaluated benchmarks with current techniques.

关键词： Duplicate detection healthcare record linkage dataset pre-processing reciprocal neuro-fuzzy inference system and ant lion optimization fuzzy system

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Designing fuzzy inference system based on improved gradient descent method

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Journal of systems Engineering and Electronics 2006年第4期17卷 853-857,863页

作者： Zhang Liquan Shao Cheng Research Center of Information and Control Dalian Univ. of Technology Dalian 116024 P. R. China

The distribution of sampling data influences completeness of rule base so that extrapolating missing rules is very difficult. Based on data mining, a self-learning method is developed for identifying fuzzy model and extrapolating missing rules, by means of confidence measure and the improved gradient descent method. The proposed approach can not only identify fuzzy model, update its parameters and determine optimal output fuzzy sets simultaneously, but also resolve the uncontrollable problem led by the regions that data do not cover. The simulation results show the effectiveness and accuracy of the proposed approach with the classical truck backer-upper control problem verifying.

关键词： data mining fuzzy system gradient descent method missing rule.

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H∞ Fault-Tolerant Guaranteed Cost Control for fuzzy system

H∞ Fault-Tolerant Guaranteed Cost Control for Fuzzy System

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2011 Chinese Control and Decision Conference（CCDC）

作者： Zhang Guoshan,Gu Xiaoyu and Feng Wenjuan are with the School of Electrical Engineering and Automation,Tianjin University.

The H∞ fault tolerant guaranteed cost control problem for a class of nonlinear system with state-delay is investigated,in which the H∞ performance index and the quadratic performance index are guaranteed simultaneously.A sufficient condition for the existence of H∞ fault-tolerant guaranteed cost controller is presented in terms of linear matrix inequality （LMI） and the optimal H∞ fault-tolerant guaranteed cost controller is *** results show the effectiveness of the proposed method.

关键词： fuzzy system T-S model H guaranteed cost control Fault-tolerant control LMI

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Prediction Model of Dissolved Oxygen fuzzy system in Aquaculture Pond Based on Neural Network

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Agricultural Science & Technology 2010年第8期11卷 14-18页

作者：王瑞梅傅泽田何有缘中国农业大学经济管理学院北京100083 中国农业大学工学院北京100083

A dissolved oxygen fuzzy system predicting model based on neural network was put forward in this study. 106 groups of data were used to confirm the fitness of the predicting model. The first 80 groups of data were acted as training input and the other 26 groups of data were acted as the confirmed data in the system. The result showed that the testing data was approximately the same as the predicted data. So it gave a new way to solve the problem that the status of the water quality couldn＇t be predicted in time and it＇s hard to watching and measuring the factors dynamic.

关键词： Aquaculture pond Dissolved oxygen fuzzy system Neural network

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Study on Prediction of Pesticide Residues Based on fuzzy system

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Agricultural Science & Technology 2016年第7期17卷 1729-1732页

作者：左帅孙景鹃于向然林坤徐奥张金超河北农业大学理学院河北省保定市071000

This study was aimed to do the prediction of pesticide residues based on fuzzy system. Taking chlorpyrifos as an example, the Mathematic fuzzy system was established by using the MRL values （maximum residue limits of all kinds of pesticides in food） of the Matlab fuzzy Toolbox to analyze and predict the degra- dation degree of pesticide residues of the same crop at different time periods of bagging treatment, with the aim to provide some theoretical guidances for solving practical problems in real life.

关键词： Pesticide residue Prediction fuzzy system Bagging Degradation

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