MATLAB BASIC Programming
Obtain a quick overview of The Math Works and MATLAB
Discuss course set-up
Evolution of the language
Features of Matlab
Working with the MATLAB User Interface
Reading and writing data
Variables and Expressions
Accessing and modifying values in variables
If - else
MATLAB® data types
Analysis and Visualization with Vectors
Calculations with vectors
Basic plot options
Analysis and Visualization with Matrices
Size and dimensionality
Calculations with matrices
File I/OOpening and closing files
Graphical User Interfaces
Designing the GUI
Programming the GUI
Our training features :
** Training session are conducted by real-time instructor with real-time examples
** Best training material
** State-of-the-art lab with required software for practicing
** Exams and Mock Interviews
** Resume preparation by expert professional s and job assistance
Importing and Visualizing Images
Objective: Import image or video frames into MATLAB and visualize them. Convert images to a format that is useful for analysis.
Interactive Exploration of Images
Objective: Explore object details such as shape, texture, and color and create a custom image exploration tool.
Objective: Perform image preprocessing operations and apply custom functions to images.
Spatial Transformation and Image Registration
Objective: Align images to use the same scale and orientation. Compare aligned images. Create a panoramic scene by stitching images.
Signal Processing MATLAB
WE shows how to analyze signals and design signal processingsystems using MATLAB, Signal Processing Toolbox™, and DSP System Toolbox.
Signals in MATLAB
Objective: Generate sampled and synthesized signals from the command line and visualize them. Create noise signals for a given specification. Perform signal processing operations like resampling, modulation, and correlation.
Creating discrete signals
Objective: Understand different spectral analysis techniques and the use of windowing and zero padding. Become familiar with the spectral analysis tools in MATLAB and explore nonparametric (direct) and parametric (model-based) techniques of spectral analysis.
Discrete Fourier transform
Linear Time Invariant Systems
Objective: Represent linear time-invariant (LTI) systems in MATLAB and compute and visualize different characterizations of LTI systems.
LTI system representations
MATLAB IEEE Projects List Mtech & Btech 2017
For more projects papers contact us Mallikarjun -
LBP-Based Segmentation of Defocus Blur
Higher-Order Image Co-segmentation
Salient Region Detection via High-Dimensional Color Transform and Local Spatial Support
Blind Super Resolution of Real-Life Video Sequences
Dense and Sparse Reconstruction Error Based Saliency Descriptor
Automatic Design of Color Filter Arrays in The Frequency Domain
Contrast Enhancement by Nonlinear Diffusion Filtering
Wavelet-Based Texture-Characteristic Morphological Component Analysis For Colour Image Enhancement
Statistical Modeling of Retinal Optical Coherent Tomography
Automatic Brain Segmentation Method based on Supervoxels
Image Denoising Using Quadtree-Based Nonlocal Means With Locally Adaptive Principal
Lossless and Reversible Data Hiding in Encrypted Images with Public Key Cryptography
A Secure Watermarking Technique Without Loss of Robustness
Printed image watermarking using direct binarys earch halftoning
Minority Costume Image Retrieval by Fusion of Color Histogram and Edge Orientation Histogram
On the Shift Value Set of Cyclic Shifted Sequences for PAPR Reduction in OFDM Systems
A Low-Complexity Architecture for PAPR Reduction in OFDM Systems with Near-Optimal Performance
Design and Performance Analysis of a Multiuser OFDM Based Differential Chaos Shift Keying
High Performance Phase Rotated Spreading Codes for MC-CDMA