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This [course_title] provides a summary of basic signals, systems and signal space in an efficient manner. You will mainly understand random signals and multi-dimensional signals. Besides, vector spaces, inner product spaces, orthogonal projections and other related concepts also discussed in this course.

Following that, learn more about sampling theorems, including the fundamentals of multi-rate signal processing. This intensive course also provides an introduction to filter banks, as well as classification of wavelets, wavelet transform, and multi-resolution analysis.


This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.


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Course Credit: NPTEL

Course Curriculum

Module: 01
Lec 01 – Introduction to signal processing 00:17:00
Lec 02 – Basics of signals and systems 00:21:00
Lec 03 – Linear time-invariant systems 00:09:00
Lec 04 – Modes in a linear system 00:22:00
Lec 05 – Introduction to state space representation 00:09:00
Module: 02
Lec 06 – State space representation 00:24:00
Lec 07 – Non-uniqueness of state space representation 00:14:00
Lec 08 – Introduction to vector spaces 00:25:00
Lec 09 – Linear independence and spanning set 00:33:00
Lec 10 – Unique representation theorem 00:19:00
Module: 03
Lec 11 – Basis and cardinality of basis 00:18:00
Lec 12 – Norms and inner product spaces 00:31:00
Lec 13 – Inner products and induced norm 00:08:00
Lec 14 – Cauchy Schwartz inequality 00:18:00
Lec 15 – Orthonormality 00:13:00
Lec 16 – Problem on sum of subspaces 00:14:00
Submit Your Assignment 00:00:00
Certification 00:00:00

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