- What is Matlab is used and where.

- Introduction of Matlab.

- Matlab advantages, disadvantages, the concept of ToolBox.

- Double String, Cell, working with the Struct data type Logical data Uint8

- Realization of basic matrix operations in Matlab

- Realization of the basic mathematical formula in Matlab

- Mathematical and logical operators

- Conditional Branching. (if, switch command)

- Loops (for, while loops)

- Array and matrix operations

- Solution of algorithmic problems

- Programs written in m-file and type in MATLAB m-function

- Numerical and analytical integral derivative calculation

- Analytical and numerical solving differential equations

- Removing the statistical properties

- Txt, Excel binary file, audio file, image file, obtaining data from stationary sources such as database and data to be sent to those resources

- Microphone, Camera Serial Parallel port, connect to peripherals such as custom data acquisition card data is sent to the real-time data acquisition and output of equipment unit

- To draw the graph of the function

- 2-D and 3-D line graphics

- Surface Graphics

- Upgrade spouse, Bar, Pie, Graphics

- Moving to prepare animations

- Numerical Differentiation, coding methods defined in the literature for Numerical Integration and implementation of these methods are available in Matlab function

- Linear and Non-Linear defined in the literature of methods for the numerical solution of equations to encode these operations and the use of ready-made MATLAB functions

- One or several variables, ordinary differential equations and coding of Partial Differential Equations with literature-defined methods and use of available function makes operations

- Unconstrained and constrained optimization algorithms to encode these operations and the use of ready-made MATLAB functions

- Be adapted to the different characteristics of functions in the coding of collected data interpolation and extrapolation techniques, the use of ready-made MATLAB functions that actions.

- Concepts of fuzzy sets and fuzzy numbers

- Membership function varieties

- Fuzzy rule bases

- Rinsing operations

- Fuzzy ANFIS neural networks (Artificial Neural Fuzzy inteface System)

- Sample applications: the diagnosis of cancer ANFIS use of the collected data

- Creating user interaction windows

- Data entry screen, error screen, create a message screen.

- File open, create saving windows Listings

- Graphical interface development environment (GUIDE)

- GUI objects

- GUI program development

- Check boxes, list boxes, combo boxes use

- Push button, radio button, toggle button application

- ActiveX operations

- Create Menu

- Sample Applications

- Neuron models and architectures

- Artificial neural network models

- Learning algorithms

- Training, validation and test steps.

- MLP, RBF, GRNN, working with SOMA architecture

- Nntool, nftool, nprtool, nctool and use nntraintool

- Case Study: Collected training data using different neural networks and testing of real-world application

- Case Study: Character recognition application

- The average of the collected data, moments, median, mode, standard deviation, variance, skewness, kurtosis covariance, removal of features such as statistical correlation

- Discrete and continuous distributions and their properties

- Expressing the distribution of the collected data and tests.

- One-dimensional and multidimensional random number generation methods.

- Markov process and random walk algorithms.

- Monte Carlo Simulation

- Statistics connected estimation methods (Bayesian method womb)

- Garch method

- Historical Method in risk calculation and variance-Kovarsanys

- Retrospective Tests

- Introduction to Simulink

- Simulink modeling

- The introduction of Simulink library

- Creation of a block diagram of an input output system

- Implementation of feedback systems with Simulink

- Realization of PID control system with Simulink

- Acceptable solution can not be resolved in time for the introduction of a difficult problem (NP-hard)

- Blind search, cross search, deep search and A * algorithm

- The definition of intuitive methods

- Genetic Algorithm (Genetic Algorithm) Particle Swarm Optimization (Partial Swarm Optimization) and Ant Colony Algorithm (Ant Colony Algorithm)

- Sample applications: traveling salesman problem, course adjustment problem, solution with an intuitive method of work-bench scheduling problems)

- The production of programs that can run on systems that have Matlab

- M-file m-function transformation

- MCC and command mbuild

- P-code compilation

- C, C ++ and Java library for use in creating

- Exe, dll and create mex files

- Reading and writing of image files

- Reading and writing of video

- Real-time image taken from the camera

- The concept of color space and color conversion

- Converting a color image to gray levels

- Gray-level official binary file conversion (threshold transactions)

- Morphological operations on binary images.

- By applying a noisy image filter cleaning

- Image smoothing and sharpening operations

- There are specific points such as corners and edges and feature extraction

- Video segment operations (segmentation)

- Character Recognition application

- Conducting depth account with dual camera

- Wavelet Applications

- There is a still from a video background

- The presence of the moving object and to follow special

- Alarm application

- The production of programs that can run on systems that have Matlab

- M-file m-function transformation

- MCC and command mbuild

- P-code compilation

- C, C ++ and Java library for use in creating

- Exe, dll and create mex files