Description: 本程序运用广义模糊神经网络理论采用MATLABL编程，实现了自适应控制-the procedures used fuzzy generalized neural network theory used MATLABL programming, the adaptive control Platform: |
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Author:容容 |
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Description: 论文标题:自适应模糊系统在手写体数字识别中的应用研究
作者:张镭
作者专业:计算机软件人工智能
导师姓名:黄战
授予学位:硕士
授予单位:暨南大学
授予学位时间:19990501
论文页数:59页
文摘语种:中文文摘
分类号:TP18 TP391.4
关键词:手写体数字 自适应 模糊逻辑 神经网络 模式识别
摘要:该文针对模式识别的特点,构造了适合于模式识别问题的自适应模糊系统,对三种不同学习算法加以改进,在手写全数字识别上对分类器进行了实现,并与采用BP算法训练的三层前馈神经网络分类器相比较,分析其优劣.仿真实验表明,在该文的样本集条件下,自适应模糊分类吕的识别性能优于神经网络分类器,这充分体现了自适应模糊技术用于数字识别的优越性和潜力.-thesis entitled : adaptive fuzzy system in a handwritten numeral recognition of applied research Author : Zhang Lei professional author : artificial intelligence computer software instructor Name : Huang war conferred degrees : Master award units : Jinan University conferred degrees : 19990501 page thesis : Abstracts 59 languages : Chinese Digest Key words : TP18-image Keywords : handwritten digital adaptive fuzzy logic neural network pattern recognition Abstract : In this paper the characteristics of pattern recognition, suitable for the construction of adaptive pattern recognition fuzzy systems, three different learning algorithm to improve the handwriting recognition on digital classification of the device to achieve, BP and with a three-tiered training algorithm for neural network clas Platform: |
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Author:成东 |
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Description: 近几年来研究的多种PID控制程序，有灰色PID，神经网络自适应PID，模糊PID等等，！
-Research in recent years a variety of PID control procedures, has gray PID, Neural Network Adaptive PID, fuzzy PID, etc.! Platform: |
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Author:wjy |
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Description: 收集了遗传算法、进化计算、神经网络、模糊系统、人工生命、复杂适应系统等相关领域近期的参考论文和研究报告-Collection of genetic algorithms, evolutionary computation, neural networks, fuzzy systems, artificial life, complex adaptive system and other related fields refer to the recent papers and research reports Platform: |
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Author:增平 |
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Description: < 控制系统计算机辅助设计--MATLAB语言与应用>>系统地介绍了国际控制界最流行的控制系统计算机辅助设计语言MATLAB，侧重于介绍MATLAB语言编程基础与技巧、数学问题的MATLAB求解、线性系统计算机辅助分析、控制系统与其他复杂系统的Simulink建模，控制系统的计算机辅助设计方法，包括串联控制器、状态反馈控制器、多变量系统频域设计、PID控制器设计、最优控制器设计、LQG/LTR控制器设计、H2=H1 最优控制、分数阶控制、自适应控制、模糊控制、神经网络控制、遗传算法优化控制等。本电子文档为其源码光盘内容，源码多多，利于学习参考。-"" Control System for Computer-Aided Design- MATLAB language and application of "" a systematic introduction to the international control of world s most popular computer-aided control system design language MATLAB, introduced the MATLAB language programming focusing on the foundation and skills, the MATLAB mathematical problem solving, computer-aided analysis of linear systems, control systems and other complex systems Simulink modeling, control system, computer-aided design methods, including serial controller, state feedback controller, multi-variable system, frequency-domain design, PID controller design, optimal controller design, LQG/LTR controller design, H2 = H1 optimal control, fractional order control, adaptive control, fuzzy control, neural network control, genetic algorithm to optimize control. This electronic document its source code CD-ROM content, source code lot, conducive to learning for reference. Platform: |
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Author:任勇 |
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Description: 文章简要介绍了模糊控制的概念和特点，并对模糊控制的原理作了说明，较详细的介绍了模糊控制的现状，包括模糊PID控制、自适应模糊控制、神经模糊控制、遗传算法优化的模糊控制、专家模糊控制等，最后对模糊控制的发展作了展望。-This paper briefly introduces the concept and characteristics of fuzzy control, and fuzzy control principle is illustrated in more detail the status of the fuzzy control including fuzzy PID control, adaptive fuzzy control, neural fuzzy control, genetic algorithm optimization of fuzzy control, expert fuzzy control, the last of the fuzzy control prospects of development. Platform: |
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Author:yaoqiuxiang |
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Description: 《机器人控制系统的设计与MATLAB仿真》一书所有的matlab仿真程序。本书系统地介绍了机器人控制的几种先进设计方法，是作者多年来从事机器人控制系统教学和科研工作的结晶，同时融入了国内外同行近年来所取得的最新成果。全书以机器人为对象，共分10章，包括先进PID控制、神经网络自适应控制、模糊自适应控制、迭代学习控制、反演控制、滑膜控制、自适应鲁棒控制、系统辨识和路径规划。-" Robot Control System Design and MATLAB simulation," a book all the matlab simulation program. This book introduces several advanced robot control design methods, is the author of the robot control system for many years engaged in teaching and research work of the crystal, while domestic and foreign counterparts into the latest achievements in recent years. Book to the robot as an object, divided into 10 chapters, including advanced PID control, neural network adaptive control, fuzzy adaptive control, iterative learning control, inversion of control, synovial control, adaptive robust control, system identification and path planning. Platform: |
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Author:Ben |
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Description: Abstract— Identifying exceptional students for
scholarships is an essential part of the admissions process in undergraduate and postgraduate institutions, and identifying weak students who are likely to fail is also important for allocating limited tutoring resources. In this article, we have tried to design an intelligent system which can separate and classify student according to learning factor and performance. a system is proposed through Lvq networks methods, anfis method to separate these student on learning factor . In our proposed system, adaptive fuzzy neural network(anfis) has less error and
can be used as an effective alternative system for classifying students. -Abstract— Identifying exceptional students for
scholarships is an essential part of the admissions process in undergraduate and postgraduate institutions, and identifying weak students who are likely to fail is also important for allocating limited tutoring resources. In this article, we have tried to design an intelligent system which can separate and classify student according to learning factor and performance. a system is proposed through Lvq networks methods, anfis method to separate these student on learning factor . In our proposed system, adaptive fuzzy neural network(anfis) has less error and
can be used as an effective alternative system for classifying students. Platform: |
Size: 299008 |
Author:Nguyen Anh Tuan |
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Description: 用MATLAB实现自适应神经模糊推理系统（ANFIS）结构训练。代码中，首先创建一个初始原ANFIS结构，然后采用遗传算法（GA）、粒子群优化（PSO）来训练ANFIS。此进化训练算法可用于解决非线性回归函数逼近问题。-Implementation of adaptive neural fuzzy inference system (ANFIS) based on MATLAB. Code, the first to create an initial original ANFIS structure, and then using the genetic algorithm (GA), particle swarm optimization (PSO) to train ANFIS. This evolutionary training algorithm can be used to solve the nonlinear regression function approximation problem. Platform: |
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Author:张贝 |
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Description: 1.elman神经网络对输入波形进行检测
2.设计具有3个神经元的Hopfield网络
3.建立自适应神经模糊推理系统对非线性函数进行逼近（正弦加滞后）
4.建立自适应神经模糊推理系统对非线性函数进行逼近（正弦多项式）
5.利用模糊C均值聚类方法将一类随机给定的三维数据分为三类(1.Detection of input waveform by elman neural network
2. design a Hopfield network with 3 neurons
3. establish adaptive neuro fuzzy inference system to approximate nonlinear functions (sine plus lag).
4. establish adaptive neuro fuzzy inference system to approximate nonlinear functions (sine polynomials).
5. fuzzy C means clustering method is used to divide a class of randomly given 3D data into three categories.) Platform: |
Size: 2048 |
Author:南风水忆 |
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Search - ADAPTIVE NEURAL FUZZY