If you are looking for Matlab projects for M.Tech students then we have a helping guide for you. MATLAB is the tool which is used to perform mathematical complex computations and it has various inbuilt tool boxes which perform required tasks according to the requirement of the user. The MATLAB use the scientific programming language to implement complex algorithms and analyze their performance in forms of numeric’s and graphs. Matlab projects for students includes – image processing, neural networks, guide, user defined interfaces are the various toolboxes which are inbuilt in the MATLAB and are used to implement algorithms. While preparing Matlab project for M.Tech students we first make them understand that the MATLAB default interface is divided into fiveparts :-

1. Command window: – The command window the first part of MATLAB which is used to display output of already saved codes and also execute MATLAB codes temporarily.
2. Workspace: – The workspace is the second part of MATLAB which is used to show variable values which are allocated in the MATLAB . The workspace is divided into three parts , variable name, variable value and variable type
3. Command history :- The command history is the another important part of MATLAB which is used to show the commands of the MATLAB which are executed previously
4. Current folder Data: The current folder contains the data which are currently saved in the folder whose path is given in the current folder path
5. Menu bar: The menu bar displays the important menus which are useful to the user for the calculation

To save the MATLAB codes user need to make the folder anywhere in the their computer and path of the folder can be given in the current folder path. The edit command is used to open the editor windows which is used to save , delete and updated the MATLAB codes. The MATLAB has high graphics which is used to analyze results in the form of graphs. The MATLAB supports three type of graphs and these graphs are bar, line and mesh graphs. Techsparks offer robust Matlab projects for M.Tech students under expert guidance to help them complete their M.Tech with flying colors.

Thesis and Research topics in Matlab

Following is the list of latest topics in Matlab for thesis, project and research work:

  1. Image Processing

  2. Signal Processing

  3. Data Compression

  4. Computer Vision

  5. Face Detection

  6. Simulink

  7. Parallel Computing

  8. Polyspace

  • Image ProcessingImage Processing is a process of performing operations on image to alter its quality, size and similar other operations. Matlab is used to perform these operations on the images. Through image processing, we can enhance the quality of image and also we can extract some useful data out of it. There are various thesis topics in image processing using Matlab. It is one of the core research areas and is growing rapidly day by day. Image Processing is of two types namely – Analogue and Digital. Digital Image Processing is the trending research area and is used to perform operations on digital images. Matlab provides tools for automation of image processing.

  • Signal Processing – Signal Processing is the process of performing operations on signals for modification and amplification. Signal processing improves the quality and efficiency of signals. Signal Processing is also of two types – Analogue and Digital. Signal Processing tools in Matlab can perform operations on the signals. These tools also provide algorithms for visualization, amplification, synchronization, and resampling. The signals can also be compared and analyzed in real-time. The main applications of digital signal processing are audio signal processing, audio compression, speech recognition, digital communication, seismology, and biomedicine. This is also a good topic for thesis implementation in Matlab.

  • Data Compression – Data Compression is the process of encoding and modifying data in such a way that it covers less memory space on the storage disk. In data compression, the number of bits is reduced than the original data. The compressed data can be sent quickly over the internet to the required destination. In this process, the repetitive elements of data and symbols are replaced and removed. This will save storage space, and reduce the cost. There are also certain algorithms designed for data compression.

  • Computer Vision – Computer Vision is a field that deals with the study to make computer highly intelligent in understanding digital images and videos. It tends to make computers visualize things just the way human visualization does. The Matlab tools provide algorithms and functions for designing and simulating computer vision. Other functions that can be performed using these tools include object detection, extraction and tracking. Along with these, Matlab also provides tools for 3D computer vision, 3D reconstruction, and 3D point cloud processing. For computer vision, machine learning and deep learning algorithms are applied. Thus, computer vision is a very good topic for research, project, and thesis in Matlab and Machine Learning.

  • Face Detection – Face Detection is another application of Matlab. There are three main processes performed in face detection – Detecting the face, Identifying the facial features, and tracking the face. Computer Vision techniques can be used for facial recognition and detection. The algorithms employed for face detection extract data from facial features and compare them to that stored in the database and find the best possible match. Face detection and recognition are used in biometrics and surveillance systems. KLT algorithm is mainly used in face detection.

  • Simulink – Simulink is a graphical programming environment provided by MatLab for modeling, simulation and analyzing. It consists of set of libraries which can be customized. With Matlab and Simulink we can combine textual programming with graphical programming to automate our system in a simulation environment. We have to simply add any one of the Matlab algorithmS from thousands of algorithms available in the Simulink block. Simulink is also a good choice for thesis topics in Matlab.

  • Parallel Computing – Parallel Computing tools help in complex computational and data-intensive problems by using multiprocessors. Multiple simulations can run in parallel by using Simulink with these tools. These help to speed up the tasks and Matlab computations. There are pattern search and hybrid functions in parallel computing.

  • Polyspace – It is a code analysis tool to detect and prove that there is no run-time error in the source code for programming languages like C, C++, and Ada. The tool also checks that whether the source code follows the appropriate coding standards. The Polyspace family include the Polyspace Code Prover and Polyspace Bug Finder. The Code Prover adds color-coding to the source code. The Bug Finder performs static code analysis on the source code to identify software bugs.

These are the latest research, thesis and project topics in Matlab for masters and postgraduate students.