This course will introduce the students to basics of signal processing and systems analysis. We will focus on continuous-time signals and systems, but also give an introduction to discrete-time signals and systems towards the end of the course. This is a very important course for all engineers working in the electronics and communications domain.
2nd year undergraduate student
Mathematics at 10+2 level
All companies dealing with signal processing
ABOUT THE INSTRUCTOR
I am an associate professor in the school of computing and electrical engineering. Before joining IIT Mandi, I did B.E. from Nirma Institute of Technology (Ahmedabad), M.Tech. from IIT Kharagpur and Ph.D. from IIT Delhi. My M.Tech. and Ph.D. theses were under the guidance of Prof. Amit Patra and Dr. Shouri Chatterjee respectively. After that I joined STMicroelectronics (Greater Noida) as a senior design engineer. After having 2 years of industrial experience, I worked with Università degli Studi di Milano as a post doctorate researcher, under the guidance of Prof. Valentino Liberali. During post-doctorate experience, I was also associated with INFN [Istituto Nazionale di Fisica Nucleare] Milano.
Dr. Kushal K. Shah completed his BTech in 2005 and PhD in 2009, both from the Electrical Engineering Department of IIT Madras. In 2009-10, he went to Weizmann Institute of Science in Israel for a post-doctoral fellowship. He joined Jawaharlal Nehru University (New Delhi) as an Assistant Professor in 2010 and in 2012, he was conferred with the GN Ramachandran fellowship by the university. In May 2012, he joined IIT Delhi as an Assistant Professor in the Electrical Engineering Department and moved to IISER Bhopal in August 2017 as an Associate Professor in the Department of Electrical Engineering & Computer Science. He was awarded the INAE Young Engineer Award in 2014. His primary research interests include Dynamical Systems, Signal Processing and Artificial Intelligence.
1. Join the course
Learners may pay the applicable fees and enrol to a course on offer in the portal and get access to all of its contents including assignments. Validity of enrolment, which includes access to the videos and other learning material and attempting the assignments, will be mentioned on the course. Learner has to complete the assignments and get the minimum required marks to be eligible for the certification exam within this period.
COURSE ENROLMENT FEE: The Fee for Enrolment is Rs. 3000 + GST
2. Watch Videos+Submit Assignments
After enrolling, learners can watch lectures and learn and follow it up with attempting/answering the assignments given.
3. Get qualified to register for exams
A learner can earn a certificate in the self paced course only by appearing for the online remote proctored exam and to register for this, the learner should get minimum required marks in the assignments as given below:
CRITERIA TO GET A CERTIFICATE
Assignment score = Score more than 50% in at least 9/12 assignments.
Exam score = 50% of the proctored certification exam score out of 100
Only the e-certificate will be made available. Hard copies will not be dispatched.”
4. Register for exams
The certification exam is conducted online with remote proctoring. Once a learner has become eligible to register for the certification exam, they can choose a slot convenient to them from what is available and pay the exam fee. Schedule of available slot dates/timings for these remote-proctored online examinations will be published and made available to the learners.
EXAM FEE: The remote proctoring exam is optional for a fee of Rs.1500 + GST. An additional fee of Rs.1500 will apply for a non-standard time slot.
5. Results and Certification
After the exam, based on the certification criteria of the course, results will be declared and learners will be notified of the same. A link to download the e-certificate will be shared with learners who pass the certification exam.
Week 1 : Mathematical Preliminaries
Week 2 : Types of Signals and Transformations
Week 3 : Fourier Transform of Continuous-Time Signals
Week 4 : Properties of Fourier Transforms
Week 5 : LTI Systems
Week 6 : Convolution and LTI System Properties
Week 7 : Laplace Transform
Week 8 : Laplace Transform Properties
Week 9 : Fourier Series of Continuous-Time Periodic Signals and Properties