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
|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|
|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|
|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|
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