MATLAB Fuzzy Logic Toolbox™ User's Guide

دانلود کتاب MATLAB Fuzzy Logic Toolbox™ User's Guide

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نام کتاب : MATLAB Fuzzy Logic Toolbox™ User's Guide
ویرایش : R2020a ed.
عنوان ترجمه شده به فارسی : راهنمای کاربر MATLAB Fuzzy Logic Toolbox™
سری :
نویسندگان : ,
ناشر : The MathWorks, Inc.
سال نشر : 2020
تعداد صفحات : 782

زبان کتاب : English
فرمت کتاب : pdf
حجم کتاب : 9 Mb



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فهرست مطالب :


Getting Started Fuzzy Logic Toolbox Product Description Key Features What Is Fuzzy Logic? Description of Fuzzy Logic Why Use Fuzzy Logic? When Not to Use Fuzzy Logic What Can Fuzzy Logic Toolbox Software Do? Foundations of Fuzzy Logic Overview Fuzzy Sets Membership Functions Logical Operations If-Then Rules References Fuzzy Inference Process Fuzzify Inputs Apply Fuzzy Operator Apply Implication Method Aggregate All Outputs Defuzzify Fuzzy Inference Diagram Membership Function Gallery Defuzzification Methods Fuzzy vs. Nonfuzzy Logic Fuzzy Inference System Modeling Mamdani and Sugeno Fuzzy Inference Systems Mamdani Fuzzy Inference Systems Sugeno Fuzzy Inference Systems Type-2 Fuzzy Inference Systems Interval Type-2 Membership Functions Type-2 Fuzzy Inference Systems Fuzzy Inference Process for Type-2 Fuzzy Systems Type-Reduction Methods Build Fuzzy Systems Using Fuzzy Logic Designer Fuzzy Logic Toolbox Graphical User Interface Tools The Basic Tipping Problem The Fuzzy Logic Designer The Membership Function Editor The Rule Editor The Rule Viewer The Surface Viewer Importing and Exporting Fuzzy Inference Systems Build Fuzzy Systems at the Command Line Build Fuzzy Systems Using Custom Functions Build Fuzzy Inference Systems Using Custom Functions in Fuzzy Logic Designer Specify Custom Membership Functions Specify Custom Inference Functions Specify Custom Type-Reduction Functions Use Custom Functions in Code Generation Fuzzy Trees Types of Hierarchical Structures Add or Remove FIS Tree Outputs Use the Same Value for Multiple inputs of FIS Tree Update Fuzzy Inference Systems in FIS Tree Tune a Fuzzy Tree Fuzzy PID Control with Type-2 FIS Fuzzy Logic Image Processing Fuzzy Inference System Tuning Tuning Fuzzy Inference Systems Tuning Methods Prevent Overfitting of Tuned System Improve Tuning Results Tune Fuzzy Rules and Membership Function Parameters Tune Fuzzy Trees Customize FIS Tuning Process Tune Mamdani Fuzzy Inference System Tune FIS Tree for Gas Mileage Prediction FIS Parameter Optimization with K-fold Cross Validation Predict Chaotic Time Series Using Type-2 FIS Tune Fuzzy Robot Obstacle Avoidance System Using Custom Cost Function Classify Pixels Using Fuzzy Systems Autonomous Parking Using Fuzzy Inference System Neuro-Adaptive Learning and ANFIS FIS Structure Training Data Training Options Display Options Training Validation Training Results Training Algorithm Differences Train Adaptive Neuro-Fuzzy Inference Systems Load Training Data Generate or Load FIS Structure Train FIS Validate Trained FIS Importance of Checking Data Save Training Error Data to MATLAB Workspace Predict Chaotic Time-Series using ANFIS Modeling Inverse Kinematics in a Robotic Arm Adaptive Noise Cancellation Using ANFIS Nonlinear System Identification Gas Mileage Prediction Data Clustering Fuzzy Clustering What Is Data Clustering? Fuzzy C-Means Clustering Subtractive Clustering References Cluster Quasi-Random Data Using Fuzzy C-Means Clustering Adjust Fuzzy Overlap in Fuzzy C-Means Clustering Fuzzy C-Means Clustering Fuzzy C-Means Clustering for Iris Data Model Suburban Commuting Using Subtractive Clustering Modeling Traffic Patterns using Subtractive Clustering Data Clustering Using Clustering Tool Load and Plot Data Cluster Data Save Cluster Centers Fuzzy Logic in Simulink Simulate Fuzzy Inference Systems in Simulink Simulate Fuzzy Inference System Access Intermediate Fuzzy Inference Results Simulation Modes Map Command-Line Functionality to Fuzzy Logic Controller Block Water Level Control in a Tank Temperature Control in a Shower Implement Fuzzy PID Controller in Simulink Using Lookup Table Deployment Deploy Fuzzy Inference Systems Generate Code in Simulink Generate Code in MATLAB Generate Code for Fuzzy System Using Simulink Coder Generate Structured Text for Fuzzy System Using Simulink PLC Coder Generate Code for Fuzzy System Using MATLAB Coder Apps Fuzzy Logic Designer Neuro-Fuzzy Designer Functions addInput addMF addOutput addRule addvar anfis anfisOptions convertfis convertToStruct convertToSugeno convertToType1 convertToType2 defuzz dsigmf evalfis evalmf fcm findcluster fuzarith gauss2mf gaussmf gbellmf genfis genfis1 genfis2 genfis3 genfisOptions gensurf gensurfOptions getfis getTunableValues getFISCodeGenerationData getTunableSettings mam2sug mf2mf mfedit newfis parsrule pimf plotfis plotmf probor psigmf readfis removeInput removeMF removeOutput rmmf rmvar ruleedit ruleview setfis setTunable setTunableValues showfis showrule sigmf smf subclust surfview trapmf trimf tunefis update writeFIS zmf Objects ClauseParameters evalfisOptions fismf fismftype2 fisrule fistree fisvar mamfis mamfistype2 MembershipFunctionSettings MembershipFunctionSettingsType2 NumericParameters RuleSettings sugfis sugfistype2 tunefisOptions VariableSettings Blocks Diff. Sigmoidal MF Fuzzy Logic Controller Fuzzy Logic Controller with Ruleviewer Gaussian MF Gaussian2 MF Generalized Bell MF Pi-shaped MF Probabilistic OR Probabilistic Rule Agg Prod. Sigmoidal MF S-shaped MF Sigmoidal MF Trapezoidal MF Triangular MF Z-shaped MF Appendices Bibliography




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