MATHWORKS SEMINAR

The MathWorks India Private Limited organized a seminar on “Design and Implement Signal Processing, Communication and Computer Vision Systems Using MATLAB and Simulink” on 4th June 2015 at Le Meridian, New Delhi. Two faculty members Prof.(Dr.) H. S. Dua and Mr. Ajit Kumar of ECE department from Dronacharya College of Engineering, Gurgaon attended Seminar.

Session 1:

Mr. Tabrez Khan, MathWorks Application Engineer conducted the session on Introduction to Signal Processing, Computer Vision and Communication System Design with MATLAB and Simulink. He started with scope and usage of the additional features included in MATLAB R2015a Version. He said that MathWorks introduces an antenna-to-bits wireless design solution. The offering helps wireless and radar system engineers simulate designs that incorporate multiple antennas, smart radio frequency (RF) devices, and advanced receiver algorithms. He added that new software-defined-radio (SDR) hardware support enables over-the-air testing with LTE and other waveforms.

He briefed about the various Simulink toolboxes with few model examples. He explained that Signal Processing Toolbox provides functions and apps to generate, measure, transform, filter, and visualize signals. The toolbox includes algorithms for resampling, smoothing, and synchronizing signals, designing and analyzing filters, estimating power spectra, and measuring peaks, bandwidth, and distortion. The toolbox also includes parametric and linear predictive modeling algorithms. He said that the Signal Processing Toolbox can be used to analyze and compare signals in time, frequency, and time-frequency domains, identify patterns and trends, extract features, and develop and validate custom algorithms to gain insight into your data.

The next topic of discussion was Multiple input, multiple output-orthogonal frequency division multiplexing (MIMO-OFDM). Mr. Khan said that it is the dominant air interface for 4G and 5G broadband wireless communications. It combines multiple input, multiple output (MIMO) technology, which multiplies capacity by transmitting different signals over multiple antennas, and orthogonal frequency division multiplexing (OFDM), which divides a radio channel into a large number of closely spaced subchannels to provide more reliable communications at high speeds. He illustrated MIMO-OFDM Wireless Communications with Beamforming, which can be designed by using Communication System, Phased Array System, DSP System and Computer Vision System toolbox. He described that MATLAB is a complete solution for solving any technical computing workflow. He further described face detection, tracking and feature extraction using Computer Vision System toolbox. He demonstrated the example of Depth Estimation using Stereo Camera, followed by documentation generation for the model using Open-CV Interface.

Session 2:

Mr. Deepak Sharma, Manager MathWorks conducted the next session on Enabling Project based Learning with Low Cost Hardware, DSP and FPGA. Firstly, he explained that project-based learning is a comprehensive teaching and learning approach that engages students in the investigation of authentic engineering problems. To make this approach effective, the teacher must identify a problem that is accessible but challenging enough to stimulate the learning process. Unfortunately, many hardware applications are too complex, distracting students from the real task with low-level hardware issues. He further added that MATLAB and Simulink address the challenge by making it easy for students to implement their projects on low-cost hardware platforms.

He next discussed on DSP. He said that the FFT and filter design are two fundamental techniques in DSP. He presented some examples of how these techniques can be used in practice can help motivate to learn the mathematical theory. He then made a thorough discussion on interfacing of Low cost hardware, DSP board, FPGA with the MATLAB for high end model generation and explained ‘Design to Implementation’ steps, which involve Research and Design, Verification, Validation and Implementation. Coder options in MATLAB provide C++ code generation for MATLAB, Simulink and Embedded blocks. Mathworks has taken many academic initiatives in respect of research training at various locations in India , MOOCs (Massive Open Online Courses) and other resources for learning The MATLAB tools were also discussed at the event.

Overall, the seminar proved very beneficial for all the participants. This event provided an opportunity to understand and recognize various new features in the MATLAB R2015a version like:

1. Desktop Documentation that integrate documentation for custom toolboxes into the MATLAB Help Browser.

2. Documentation that determine when feature introduced,

3. Array Size Limit that limit maximum array size to prevent unintended creation of very large matrices.

4. Tab Completion that complete class properties and methods while editing class definition files

5. User Interface Preferences that control user interface language