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Start 4 June 2026 07:06
Einde 4 June 2026
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Overzicht
Master MATLAB's comprehensive capabilities from basic matrix operations to advanced applications in scientific computing, data visualization, simulation, and machine learning implementations.
Lesprogramma
- Charpter 1 MATLAB Introduction
- Charpter 2 The Matrix and Its Operation
- Charpter 3 MATLAB Program Structure and M file
- Charpter 4 Polynomial Operation and Data Processing
- Charpter 5 Language Symbol Operation
- Charpter 6 Data Visualization
- Charpter 7 Simulink Simulation Foundation
- Charpter 8 Regression Analysis
- Charpter 9 Genetic Algorithm and Its MATLAB Implementation
- Charpter 10 Artificial Neural Network and Its MATLAB Implementation
- Charpter 11 Deep learning and Its MATLAB Implementation
- Chapter 12 Reinforcement learning and Its MATLAB Implementation
- Charpter 13 Adanced simulink applications
- 期末考试
1.1 The introduction of MATLAB environment
1.2 Data types and basic operations
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
3.1 Sequence program structure
3.2 M file
3.3 M function file
4.1 Polynomial operation
4.2 Data interpolation and fitting
4.3 Data statistics
4.4 Numerical calculation
5.1 Creation and application of MATLAB symbolic objects
5.2 Symbolic polynomial function operation
6.1 2D curves and graphs
6.2 2D curves format setting
6.3 2D Special Drawing
6.4 3D curves and surfaces
7.1 Overview of Simulink
7.2 The application of Simulink
7.3 Simulink simulation
8.1 Principle of least squares method
8.2 Linear Regression and Its MATLAB Applications
8.3 Non-Linear Regression and Its MATLAB Application
9.1 The Principle of Genetic Algorithm
9.2 The Application of Genetic Algorithm in MATLAB
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
11.1 Basic concepts of deep learning
11.2 Introduction to convolutional neural network (CNN)
11.3 CNN algorithm 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
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
Gegeven door
Ni Yanting
Vakgebieden
Programming