MATLAB and Scientific Computation

Übersicht

Master MATLAB's comprehensive capabilities from basic matrix operations to advanced applications in scientific computing, data visualization, simulation, and machine learning implementations.

Lehrplan

• Charpter 1 MATLAB Introduction
1.1 The introduction of MATLAB environment
1.2 Data types and basic operations
• Charpter 2 The Matrix and Its Operation
2.1 The creation of the Matrix
2.2 The modification of the Matrix
2.3 The basic operations of Matrix
2.4 The analysis of the Matrix
• Charpter 3 MATLAB Program Structure and M file
3.1 Sequence program structure
3.2 M file
3.3 M function file
• Charpter 4 Polynomial Operation and Data Processing
4.1 Polynomial operation
4.2 Data interpolation and fitting
4.3 Data statistics
4.4 Numerical calculation
• Charpter 5 Language Symbol Operation
5.1 Creation and application of MATLAB symbolic objects
5.2 Symbolic polynomial function operation
• Charpter 6 Data Visualization
6.1 2D curves and graphs
6.2 2D curves format setting
6.3 2D Special Drawing
6.4 3D curves and surfaces
• Charpter 7 Simulink Simulation Foundation
7.1 Overview of Simulink
7.2 The application of Simulink
7.3 Simulink simulation
• Charpter 8 Regression Analysis
8.1 Principle of least squares method
8.2 Linear Regression and Its MATLAB Applications
8.3 Non-Linear Regression and Its MATLAB Application
• Charpter 9 Genetic Algorithm and Its MATLAB Implementation
9.1 The Principle of Genetic Algorithm
9.2 The Application of Genetic Algorithm in MATLAB
• Charpter 10 Artificial Neural Network and Its MATLAB Implementation
10.1 Basic concepts of neural networks
10.2 The principle of BP neural network
10.3 The Application of BP Neural Network in MATLAB
• Charpter 11 Deep learning and Its MATLAB Implementation
11.1 Basic concepts of deep learning
11.2 Introduction to convolutional neural network (CNN)
11.3 CNN algorithm and its MATLAB implementation
• Chapter 12 Reinforcement learning and Its MATLAB Implementation
12.1 The principles of Reinforcing Learning (RL)
12.2 An introduction to the main algorithms for reinforcement learning
12.3 The application of Reinforcement learning in MATLAB
• Charpter 13 Adanced simulink applications
13.1 Simulink and Materab Interface Technology
13.2 Design and adjustment of PID controller I
13.3 Design and adjustment of PID controller II
13.4 Simulink Simulation of Dynamic Systems
13.5 Simulink Simulation Technology
• 期末考试

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Unterrichtet von

Ni Yanting

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Fachgebiete

Programming