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| موضوع: كتاب Mastering MATLAB - A Comprehensive Journey Through Coding and Analysis الثلاثاء 11 يونيو 2024, 12:19 am | |
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أخواني في الله أحضرت لكم كتاب Mastering MATLAB - A Comprehensive Journey Through Coding and Analysis Kameron Hussain and Frahaan Hussain
و المحتوى كما يلي :
TABLE OF CONTENTS Title Page Copyright Page Mastering MATLAB: A Comprehensive Journey Through Coding. and AnalysisTable of Contents Chapter 1: Introduction to MATLAB 1.1 Understanding the MATLAB Environment What is MATLAB? Launching MATLAB The MATLAB Workspace Command Line vs. Scripting Help and Documentation 1.2 History and Evolution of MATLAB Early Beginnings MATLAB’s Commercialization Growth and Expanding Capabilities Graphical User Interface (GUI) Advancements in Parallel Computing. Modern Era and Beyond1.3 Basic Syntax and Operations MATLAB Syntax Variables and Assignments Basic Operations Comments Built-in Functions Displaying Results Scripting and Functions 1.4 MATLAB vs. Other Programming Languages High-Level vs. Low-Level Languages Numerical Computing Focus Interactivity and Quick Prototyping Extensive Toolbox Support Simplicity of Syntax Integration with Other Languages License and Cost1.5 Setting Up and Navigating the MATLAB Interface Launching MATLAB MATLAB Desktop Creating and Running MATLAB Scripts MATLAB Documentation and Help Customizing MATLAB Online Community and Resources Closing MATLAB Chapter 2: Fundamental Programming Concepts 2.1 Variables and Data Types Variables in MATLAB Data Types Variable Assignment and Naming Conventions Displaying Variables Clearing Variables Checking Variable Type2.2 Operators and Expressions Arithmetic Operators Relational Operators Logical Operators Assignment Operators Operator Precedence 2.3 Control Structures: If-Else, Switch-Case Conditional Statements Nested if-else Statements Logical Operators in Conditionals Using break and continue 2.4 Loops: For and While The for Loop The while Loop Loop Control Statements Vectorization and Efficiency2.5 Functions and Script Files Functions in MATLAB Script Files in MATLAB Function vs. Script Chapter 3: Advanced Programming Techniques 3.1 Writing Efficient MATLAB Code Vectorization Preallocation Avoiding Global Variables Profiling and Optimization Parallel Computing. Memory Management Efficient Algorithms 3.2 Debugging and Error Handling. Debugging Techniques Error Handling.Common Debugging Scenarios 3.3 Object-Oriented Programming in MATLAB Classes and Objects Inheritance Encapsulation and Access Control Benefits of Object-Oriented Programming 3.4 Graphical User Interface Development MATLAB’s GUI Development Tools GUIDE-Based GUI Development Programmatic GUI Development Benefits of GUI Development in MATLAB 3.5 Integrating MATLAB with Other Languages Interoperability with C/C+ + Integration with Python Java Integration MATLAB Engine APIsWeb Services and REST APIs Benefits of Integration Chapter 4: Mathematical Operations and Techniques 4.1 Matrix and Vector Operations Basics of Matrices and Vectors Solving Linear Systems Eigenvalue and Eigenvector Computations Singular Value Decomposition (SVD) 4.2 Linear Algebra Applications Solving Systems of Linear Equations Eigenvalue Problems Singular Value Decomposition (SVD) Linear Transformations and Geometry Applications in Machine Learning. 4.3 Differential Equations and IntegrationSolving Ordinary Differential Equations (ODEs) Solving Partial Differential Equations (PDEs) Integration Techniques 4.4 Fourier Transforms and Signal Processing Discrete Fourier Transform (DFT) Inverse Fourier Transform Spectrogram and Short-Time Fourier Transform (STFT) Filtering and Signal Processing. Fast Fourier Transform (FFT) for Efficiency 4.5 Optimization Techniques Linear Programming (LP) Nonlinear Optimization Global Optimization Mixed-Integer Linear Programming (MILP) and Mixed-Integer Nonlinear Programming (MINLP)Chapter 5: Data Analysis and Visualization 5.1 Importing and Exporting Data Importing Data Exporting Data Data Exploration and Preprocessing. Data Visualization 5.2 Data Cleaning and Preprocessing Handling Missing Data Data Transformation Data Aggregation and Resampling. Handling Categorical Data Data Validation 5.3 Statistical Analysis with MATLAB Descriptive Statistics Hypothesis Testing. Regression AnalysisTime Series Analysis Data Distributions and Probability Multivariate Analysis 5.4 Creating Plots and Graphs Basic Plotting. Scatter Plots Bar Charts Histograms Box Plots 3D Plots Customizing Plots 5.5 Advanced Visualization Techniques Geographic Data Visualization 3D Visualization Interactive Plotting with App Designer AnimationCustom Plot Interactions Specialized Visualization Toolboxes Chapter 6: Simulink: An Introduction 6.1. Overview of Simulink Simulink Basics Block Diagram Modeling Simulation and Analysis MATLAB Integration Targeting Hardware Application Areas 6.2. Simulink vs. MATLAB: Understanding the Differences Purpose and Usage Modeling Paradigm Representation of Systems Simulation and Analysis Customization and ExtensibilityTarget Applications Integration 6.3. Basic Simulink Models Blocks in Simulink Connecting Blocks Parameters and Block Configuration Simulink Canvas Example: Simple Mass-Spring-Damper System 6.4. Simulating Dynamic Systems Setting Up Simulations Defining Input Signals Simulating the System Analyzing Simulation Results Example: Pendulum Simulation 6.5. Simulink for Control Systems Control System Modeling.Controller Design Simulation and Analysis Control System Tuning. Real-Time Testing and Hardware-in-the-Loop (HIL) Example: Quadcopter Control Chapter 7: Specialized MATLAB Toolboxes 7.1. Image Processing Toolbox Basic Image Operations Filtering and Noise Reduction Image Segmentation Morphological Operations Object Analysis and Measurements Advanced Image Processing. Computer Vision and Machine Learning. 7.2. Signal Processing Toolbox Signal AnalysisFiltering and Filtering Design Spectral Analysis Time-Frequency Analysis Filter Banks and Multirate Signal Processing. Signal Processing for Communications Real-World Applications 7.3. Financial Toolbox Financial Instruments Risk Assessment and Management Financial Modeling. Time Series Analysis Financial Economics Real-World Applications 7.4. Robotics Toolbox Robot Modeling Robot ControlKinematic and Dynamic Analysis Visualization and Simulation Real-World Applications 7.5. Machine Learning Toolbox Data Preprocessing. Supervised Learning Unsupervised Learning. Deep Learning. Model Evaluation Deployment and Integration Real-World Applications Chapter 8: Scientific Computing with MATLAB 8.1. Computational Biology Sequence Analysis Genomic Data Analysis Protein Structure and FunctionSystems Biology Data Visualization Resources and Toolboxes Real-World Applications 8.2. Chemical Engineering Applications Process Modeling and Simulation Optimization and Design Data Analysis and Visualization Chemical Engineering Toolboxes Real-World Applications 8.3. Physics Simulations Numerical Simulations Computational Physics Mathematical Tools Visualization and Analysis Computational Tools and ToolboxesReal-World Applications 8.4. Mathematics and Computational Algorithms Mathematical Computations Computational Algorithms Mathematical Modeling. Advanced Mathematical Capabilities Coding and Scripting. Real-World Applications 8.5. Environmental Science Modeling Data Analysis and Processing. Mathematical Modeling and Simulation GIS Integration Environmental Monitoring and Management Visualization and Reporting. Case Studies Chapter 9: MATLAB for Engineers9.1. Electrical Engineering Applications Circuit Analysis and Design Signal Processing and Communication Electrical Machine Analysis Power Systems Analysis Renewable Energy Systems Hardware-in-the-Loop (HIL) Testing. Robotics and Automation Electromagnetic Analysis 9.2. Mechanical Engineering Simulations Finite Element Analysis (FEA) Multibody Dynamics Structural Analysis and Design 9.3. Civil Engineering and MATLAB Structural Analysis and Design Geotechnical Engineering.Transportation Engineering. Environmental Engineering. Project Management and Optimization 9.4. Aerospace Engineering: Modeling and Analysis Aircraft and Spacecraft Design Flight Dynamics and Control Orbital Mechanics and Space Missions Structural Analysis and Materials Propulsion Systems and Rocketry 9.5. Automotive Engineering: Modeling and Analysis Vehicle Dynamics and Handling. Powertrain and Engine Simulation Control System Design Autonomous and Connected Vehicles Noise, Vibration, and Harshness (NVH) Analysis Data Analysis and Testing.10.1. Writing Academic Papers with MATLAB Figures Benefits of Using MATLAB for Academic Figures Creating Publication-Quality Figures in MATLAB Including MATLAB Figures in Academic Documents 10.2. MATLAB in Thesis and Dissertation Research Data Analysis and Visualization Simulation and Modeling Writing and Documentation Collaboration and Presentation 10.3. Collaborative Research Using MATLAB Version Control with Git Sharing Code and Data Simulink Collaboration Real-Time Collaboration 10.4. Data Management and Archiving. Organizing DataVersion Control for Data Data Archiving. Data Licensing. Data Privacy and Ethics 10.5. Ethical Considerations in Computational Research 1. Data Privacy and Security 2. Research Integrity 3. Responsible AI and Machine Learning. 4. Inclusivity and Accessibility 5. Ethical Use of MATLAB Toolboxes 6. Collaboration and Attribution 7. Compliance with Regulations 8. Ethics Review Chapter 11: Scripting and Automation Section 11. 1: Automating Repetitive Tasks Writing MATLAB ScriptsDefining MATLAB Functions Control Structures for Automation Automation in MATLAB Projects Section 11. 2: Building Custom Functions Defining Custom Functions Input and Output Arguments Local Variables Best Practices Section 11. 3: Batch Processing with MATLAB Understanding Batch Processing. Example: Batch Processing Data Files Custom Analysis Function Batch Processing Advantages Section 11. 4: Scheduler and Time-Based Operations Timer Objects Scheduled TasksReal-Time Data Acquisition Task Scheduling. Task Scheduler Toolbox Section 11. 5: Interfacing with Databases Database Connectivity Querying the Database Updating Database Records Error Handling. Closing the Database Connection Chapter 12: MATLAB for Business and Finance Section 12. 1: Analyzing Financial Markets Data Retrieval Data Visualization Technical Analysis Portfolio Optimization Backtesting Trading StrategiesRisk Management Section 12. 2: Risk Management Models Value at Risk (VaR) Conditional Value at Risk (CVaR) Portfolio Risk Metrics Stress Testing Monte Carlo Simulation Section 12. 3: Econometrics and Economic Modeling. Time Series Analysis Economic Modeling. Economic Data Visualization Economic Forecasting Section 12. 4: Operations Research and Optimization Linear and Nonlinear Optimization Integer Programming Network OptimizationSection 12. 5: Business Intelligence and Data Analysis Data Exploration Statistical Analysis Predictive Analytics Interactive Reporting. Chapter 13: Machine Learning and AI with MATLAB Section 13. 1: Introduction to Machine Learning in MATLAB Understanding Machine Learning. Getting Started with MATLAB for Machine Learning Example of Supervised Learning in MATLAB Section 13. 2: Supervised Learning Techniques in MATLAB Classification and Regression Example: Classification with MATLAB Regression with MATLAB Section 13. 3: Unsupervised Learning Approaches in MATLAB Clustering TechniquesDimensionality Reduction Anomaly Detection Section 13. 4: Deep Learning and Neural Networks in MATLAB Deep Learning Toolbox Deep Learning Applications Deep Learning Visualization and Analysis Section 13. 5: Natural Language Processing with MATLAB Text Processing. Sentiment Analysis Text Classification Language Translation Chatbot Development Text Generation Section 14. 1: Digital Signal Processing Fundamentals Understanding Signals Signal Representation in MATLABSignal Visualization Signal Operations Spectral Analysis Section 14. 2: Image Enhancement and Filtering. Image Enhancement Techniques Image Filtering Displaying Enhanced Images Section 14. 3: Feature Extraction Techniques Edge Detection Blob Detection Corner Detection Texture Analysis Color Histograms Fourier Transform for Frequency Features Section 14. 4: Computer Vision with MATLAB Image Processing ToolboxObject Detection and Recognition Optical Character Recognition (OCR) Motion Detection and Tracking. 3D Vision and Stereo Vision Augmented Reality (AR) Section 14. 5: Audio Processing and Analysis with MATLAB Importing and Reading Audio Files Basic Audio Manipulations Audio Spectrogram and Visualization Speech Recognition Audio Effects and Filters Music Analysis and Beat Detection Real-Time Audio Processing Chapter 15: Biomedical Applications of MATLAB Section 15. 1: Biomedical Signal Processing Importing and Visualizing Biomedical SignalsFiltering and Denoising. Feature Extraction Heart Rate Variability Analysis EEG Signal Processing. Integration with Machine Learning. Section 15. 2: Medical Image Analysis Image Preprocessing. Segmentation Feature Extraction Image Registration 3D Image Analysis Deep Learning for Medical Image Analysis Section 15. 3: Modeling Biological Systems Biochemical Reaction Modeling. Biological Network Modeling Pharmacokinetic Modeling.Section 15. 4: Bioinformatics with MATLAB Sequence Analysis Structural Biology Genomics and Transcriptomics Metabolomics and Systems Biology Next-Generation Sequencing (NGS) Data Analysis Section 15. 5: Biomechanics and Movement Analysis Motion Capture and Analysis Finite Element Analysis (FEA) Muscle Simulation Ergonomics and Human Factors Sports Biomechanics Rehabilitation Engineering. Chapter 16: MATLAB in the Internet of Things (IoT) Section 16. 1: Connecting MATLAB to IoT Devices Section 16. 2: Data Acquisition from SensorsSection 16. 3: Analyzing loT Data Section 16. 4: Predictive Maintenance Using MATLAB Section 16. 5: Cloud Integration and Data Storage Solutions Chapter 17: High-Performance Computing with MATLAB Section 17. 1: Parallel Computing in MATLAB Benefits of Parallel Computing in MATLAB Types of Parallelism in MATLAB Example of Multi-Core Parallelism in MATLAB Section 17. 2: GPU Acceleration Techniques in MATLAB Benefits of GPU Acceleration GPU Support in MATLAB Example of GPU Acceleration in MATLAB When to Use GPU Acceleration Section 17. 3: Large-Scale Data Handling in MATLAB 1. Tall Arrays 2. Datastore and Parallel Computing.3. Database Connectivity 4. Memory-Mapped Files 5. Distributed Computing. Section 17. 4: Distributed Computing and MATLAB 1. Parallel Computing Toolbox 2. Parallel Data Processing 3. Distributed Computing on Clusters 4. Task Synchronization 5. Scaling and Load Balancing Section 17. 5: Performance Optimization Strategies 1. Vectorization 2. Preallocation 3. Memory Management 4. Algorithm Selection 5. Parallel Computing 6. Profiling and Benchmarking.7. Mex Files 8. Optimized Libraries and Toolboxes 9. Hardware Acceleration 10. Code Review and Optimization Chapter 18: Case Studies and Real-World Applications Section 18. 1: Case Study: Environmental Monitoring System Introduction Problem Statement MATLAB Implementation Benefits Conclusion Section 18. 2: Case Study: Financial Forecasting Model Introduction Problem Statement MATLAB Implementation BenefitsConclusion Section 18. 3: Case Study: Autonomous Vehicle Algorithms Introduction Problem Statement MATLAB Implementation Benefits Conclusion Section 18. 4: Case Study: Medical Diagnostic Software Introduction Problem Statement MATLAB Implementation Benefits Conclusion Section 18. 5: Case Study: Smart Grid Energy Analysis Introduction Problem StatementMATLAB Implementation Benefits Conclusion Chapter 19: Best Practices and Tips for MATLAB Users Section 19. 1: Effective Coding Practices Section 19. 2: Documentation and Code Sharing 1. Function Headers and Comments 2. Usage Examples 3. MATLAB Publishing 4. GitHub and Version Control 5. ReadMe Files 6. Documentation Generators 7. Online Platforms and Forums 8. Licensing and Permissions 9. Collaboration and Contribution Guidelines 10. Update and MaintainSection 19. 3: Community and Online Resources 1. MATLAB Central 2. Stack Overflow 3. GitHub 4. MATLAB Documentation and Tutorials 5. Online Courses and MOOCs 6. YouTube Tutorials 7. LinkedIn Groups 8. Research Papers and Journals 9. Contribute to Open Source 10. MathWorks Support Section 19. 4: Career Opportunities and MATLAB Certification Career Opportunities MATLAB Certification Section 19. 5: Continuing Education and Learning Paths The Importance of Continuing EducationMATLAB Learning Paths Chapter 20: The Future of MATLAB Section 20. 1: Emerging Trends in MATLAB Programming. 1. Interoperability with Other Languages 2. Enhanced AI and Machine Learning Capabilities 3. Cloud Integration and Scalability 4. GPU Acceleration and High-Performance Computing. 5. Explainable AI and Ethical Considerations 6. Integration with IoT and Sensor Data 7. Advancements in Simulink 8. Sustainability and Green Technologies 9. Education and Accessibility 10. Community Collaboration and Open Source Section 20. 2: Future of Computational Sciences with MATLAB 1. Multidisciplinary Research 2. Quantum Computing.3. Computational Chemistry and Materials Science 4. Climate Modeling and Environmental Studies 5. Personalized Medicine 6. Space Exploration and Astronomy 7. Cybersecurity and Data Privacy 8. Fusion of AI and Scientific Computing 9. Human-Machine Collaboration 10. Educational Advancements Section 20. 3: MATLAB in Space Exploration and Astronomy 1. Mission Planning and Navigation 2. Data Analysis and Image Processing. 3. Simulating Celestial Phenomena 4. Telescope Control and Automation 5. Gravitational Wave Analysis Section 20. 4: The Role of MATLAB in Sustainable Technologies 1. Renewable Energy Systems2. Electric Vehicle (EV) Development 3. Sustainable Agriculture 4. Environmental Monitoring. 5. Sustainable Building Design Section 20. 5: MATLAB and the Advancement of AI and Machine Learning. 1. Deep Learning Frameworks 2. Data Preparation and Preprocessing. 3. Machine Learning Model Development 4. Explainable AI and Interpretability 5. Deployment and Integration 6. AutoML and Hyperparameter Tuning. 7. Research and Innovation #ماتلاب,#متلاب,#Matlab,#مات_لاب,#مت_لاب,
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