M. Tech. in Signal Processing and Embedded Systems is a program offered at School of Engineering, Amrita Vishwa Vidyapeetham, Amritapuri campus.
Applications involving the knowledge of embedded systems are evolving day by day. No system design is complete without a comprehensive understanding and treatment of signal processing. This unique M.Tech. Program is designed to offer not only in-depth theoretical knowledge in the areas of Embedded systems and programming, but also in the domain of signal processing. Such courses are the need of the hour and fall in-line with the expectations and requirements of the core companies. At the end of the programme, the student would be equipped with:
|FC||Mathematical Foundations (Linear algebra, Prob. Random Proc.)||3||1||0||4|
|FC||Discrete Mathematics and Algorithms||3||1||0||4|
|SC||Digital Signal Processing||3||1||0||4|
|SC||Theory of Computing||3||0||0||3|
|SC||Embedded Systems Lab||0||0||4||2|
|SC||Digital Signal Processing Lab||0||0||4||2|
|Programming Lab I (C++)||0||0||2||1|
|HU||Amrita Values Program*||P/F|
|HU||Career Competency I*||P/F|
|SC||RTOS for Embedded
|SC||Statistical Signal Processing||3||1||0||4|
|FC||Programming Lab I I(Python)||0||0||
|HU||Career Competency II||P/F|
|SEMESTER IV (Project Work)|
|Total Credits (24+24+6+10) = 64|
|L - Lecture | T - Tutorial | P - Practical | FC - Foundation Core | SC - Subject Core | E - Electives | P - Dissertation | P/F - Pass/Fail|
Elective courses will include all electives but not restricted to following domains:
Signal Processing: E.g. Biomedical Signal Processing, Image Processing, Speech Processing, Video Processing, Wavelet based Signal Processing, Pattern Recognition, Deep Learning Techniques for Signal processing, Multirate Signal Processing for Communication Systems, Cryptography, etc.
Embedded and Computing: FPGA based System design, Distributed Computing, Embedded Processor Architectures, GPU Architecture and Programming, Hardware Software Co-Design, Object Oriented Programming, Algorithms and Structures for Data Science, Embedded Computing for Data Science, Internet of Things, etc.
Communication: Digital Communication, Wireless Communication, Information Theory and Coding, Networking and Data Communication, Wireless sensor Networks, etc.