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Technical computing uses MATLAB, a very high-performance language. It describes the issue and solution in a well-known mathematical notation and unifies computation, visualisation, and programming inside a language. The term “Matrix Laboratory” is the source of the name “MATLAB.” Engineers and scientists utilise it as a platform for data analysis, algorithm development, and model creation.
MATLAB provides live editing platforms where engineers and scientists may write scripts that mix output in an executable notebook with code-formatted text, allowing users to put their ideas into practice. To run the algorithms on the embedded processor, MATLAB also assists in automatically translating the algorithms to CUBA HDL and C/C++ code.
Know about MATLAB
The programming language MATLAB enables the manipulation, construction, and operation of data, algorithms, and user interfaces used in a variety of applications. An extremely powerful language for technical computing is called MATLAB. Candidates must be proficient in programming and have completed comparable coursework at the bachelor’s or master’s level to be eligible.
MATLAB is a great tool for teaching and conducting research because of these capabilities. With the aid of the highly technical programming language MATLAB, issues involving the manipulation of numbers may be solved by writing moderate-sized programmes.
How Do MATLAB Courses Work?
A technical computer course called MATLAB contains instruction in a high-performance language. The Linpack (Linear System Package) and EISPACK (Eigen System Package) projects’ matrix software are readily available through MATLAB.MATLAB is a recently created programming language with an advanced data structure, built-in toolkits, and support for object-oriented programming.
Who is eligible for MATLAB courses?
Engineering and science graduates and professionals are more suited for MATLAB programming. Additionally, someone with a background in mathematics or statistics may pick up MATLAB programming quickly.
The individual who is pursuing a PhD in mathematics, physics, or engineering typically chooses the MATLAB course. They favour using MATLAB as their preferred computer programming language above other widely used languages like Java and C/C++.
Why take courses in MATLAB?
Scientists, educational institutions, and individuals interested in researching certain subjects were the major users of MATLAB.
The following computer problems are resolved with the use of MATLAB courses:
- For programming, modelling, and data analysis
- To handle and visualise data. It also aids in the automation of data analysis chores and the creation of customised visuals.
- MATLAB programming methods are used
- MATLAB programming is used for image processing.
Professionals wishing to undertake some exclusive work should take MATLAB classes. A career in MATLAB is an option for someone who enjoys programming. Programming with MATLAB is helpful for both programming in mechanical engineering and mathematical research.
IIndustrial Training in MATLAB is a modular 6 Months course. The course curriculum of Industrial Training in MATLAB comprises of
MATLAB Course
- Introduction to MATLAB
- Historical Background
- Applications
- Scope of MATLAB
- Importance to Engineers
- Features
- MATLAB Windows (Editor, Work space, Command history, Command Window)
- Operations with variables
- Naming and Checking Existence
- Clearing Operations
- Matrix Operations & Operators
- Reshaping Matrices
- Importing Exporting Of Data
- Arrays
- Data types
- File Input-Output
- Communication with external devices
- Writing script files
- writing functions
- Error Correction
- M-Lint Automatic Code Analyzer
- Saving files
- Flow control
- Conditional Statements
- Error Handling
- Work with multidimensional array
- Cell Array & Characters
- Developing user defined function
- Scripts and other Functions
- Basic Technical Level Computing with MATLAB
- Simple graphics
- Graphic Types
- Plotting functions
- Creating plot &Editing plot (2D and 3D)
- Graphics Handles
- GUI (Graphical User Interface)
- Introduction
- Importance
- Model Based Design
- Tools
- Mathematical Modeling
- Converting Mathematical Model into Simulink Model
- Running Simulink Models
- Importing Exporting Data
- Solver Configuration
- Masking Block/Model
- Basic Technical Level Computing with MATLAB
- General instructions
- Create linear models
- Classes of Control System Toolbox
- Discussion on state space representation
- Transfer function
- System gain and dynamics
- Time & Frequency domain analysis
- Classical design, State Space Model
- Transfer function representation, System response
- LTI viewer detail and explanation about LTI viewer
- Designing of compensator
- Use of SISO design
- Basics of Signal Processing
- Representing Signals
- Analysis of different Signals
- Complex Signals
- Filter Designing
- Using the Filter Designing GUIs
- Analyzing the filter plots
- Filter Designing using Script Files
- Speech Recording
- Speech Processing
- Other Signal Processing Functions
- Signal Sources
- BER Tool
- Modulation
- Special Filter
- Channels
- Equalizers
- Reading and Writing Image Data
- Displaying and Exploring Image
- Spatial Transformation
- Image Registration
- Designing and implementing 2D linear Filters for Image Data
- Morphological Operations
- Transforms
- Analyzing and Enhancing Images
- ROI based Processing
- Neighborhood and Block operations
- Input, Output, and Conversions
- Display and Graphics
- Registration and Stereo Vision
- Motion Estimation and Tracking
- Geometric Transformations
- Filters, Transforms, and Enhancements
- Basic introduction to fuzzy logic
- Fuzzy Versus Non-fuzzy Logic
- Foundations of Fuzzy Logic
- Fuzzy Inference Systems
- Building Systems with Fuzzy Logic Toolbox Software
- Building Fuzzy Inference Systems Using Custom Functions
- Working from the Command Line
- Working in Simulink Environment
- Simulating Fuzzy Inference Systems Using the Fuzzy Inference Engine
- Network Objects, Data, and Training Styles
- Multilayer Networks and Backpropagation Training
- Control Systems
- Radial Basis Networks
- Self-Organizing and Learning
- Vector Quantization Nets
- Adaptive Filters and Adaptive Training
- Stateflow Chart Concepts
- Stateflow Chart Notation
- Stateflow Chart Semantics
- Building Mealy and Moore Charts
- Using Actions in Stateflow Charts
- Stateflow Design Patterns
- Truth Table Functions for Decision-Making Logic
- Using Simulink Functions in Stateflow Charts
- Debugging and Testing Stateflow Charts
- Exploring and Modifying Charts
- Semantic Rules Summary
- Semantic Examples
- C/C++ Source MEX-Files
- Examples of C/C++ Source MEX-Files
- Debugging C/C++ Language MEX-Files
- Handling Large mxArrays
- Memory Management
- Large File I/O
- Basic components of Embedded System
- Hardware Classification of Embedded System
- Programming Language Classification of Embedded System
- Advantage & Disadvantage of Low level & High level Programming Languages.
- Type of Microcontroller
- Memory Classification
- Assembler
- Interpreter
- Compiler
- Simulator
- Emulator
- Debugger
- Classification of Von-Neumann and Harvard Architecture
- Difference between RISC and CISC
- Memory Classification (Primary & Secondary)
- Data Transfer Instructions
- Arithmetic Instructions
- Logical Instructions
- Conditional Instructions
- Led Interfacing
- 7 Segment Display Types
- 7 Segment Interfacing
- Introduction to Motors
- DC Motor Interfacing
- Stepper Motor Interfacing
- Introduction to Sensing Devices
- Different Type of Sensors
- Introduction to Arduino Boards and Shields
- Arduino IDE Introduction
- Programming in Arduino
- Arduino Interfacing With MATLAB
- Led Interfacing
- 7 Segment Interfacing
- DC motor Interfacing
- Stepper motor Interfacing
- Arduino Interfacing With Simulink
- Standalone Application Development Using Simulink
- Need, Scope, Use and History of VLSI.
- Introduction to Chip Design Process.
- Description of Hardware Description Languages.
- Applications of VLSI
- Top Down Design Methodology
- Bottom Up Design Methodology
- Design Process and Steps.
- Design Simulation and Design Synthesis.
- Introduction to VHDL
- Introduction to Verilog HDL
- Difference between Verilog HDL & other Programming HDL’s
- Different Tools Available in Industry
- Working on Xilinx Project Navigator
- Working on Simulator
- Gate Level Modeling Style
- Data Flow Modeling Style
- Behavioral Modeling Style
- Switch Level Modeling Style
- Module
- Initials
- Always
- Data Types
- FPGA
- CPLD
- RTL
- MATLAB HDL Coder
- Code Generation using HDL coder in MATLAB
- Learning MATLAB TOOL related programming
- Fixed point conversions
- HDL code generations
- Synthesize Code from MATLAB to Verilog HDL
- Learning MATLAB HDL Verifier
- Learning ModelSim using MATLAB
- Using MATLAB HDL Verifier to operate FPGA in Loop.
The highlight of the MATLAB Course
- Introduction to MATLAB
- Creating variables
- Data types
- Lectures
- Script files
- Introduction to array
- Graphing
- Input statements
- Output statements
- Conditional statements
- Logical operators
- Loops and arrays functions
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| MATLAB Course Fee and Duration | |||
|---|---|---|---|
| Track | Regular Track | Weekend Track | Fast Track |
| Course Duration | 150 - 180 days | 28 Weekends | 90- 120 days |
| Hours | 2 hours a day | 3 hours a day | 6+ hours a day |
| Training Mode | Live Classroom | Live Classroom | Live Classroom |
