Adaptive signal Processing
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Follow on Instagram for UpdatesAdaptive signal Processing Syllabus — Unit-wise Content
The official GTU curriculum for Adaptive signal Processing (subject code 2732702) as prescribed for EAC( · Semester 3 divides the course into 5 units, covering 28 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (2732702)Unit 1 Discrete random processes
- Random variables
- random processes
- filtered random processes
- Ensemble averages
- power spectrum
- cross power spectrum
- time averages
- biased & unbiased estimators
- consistent estimators
Unit 2 Linear prediction
- Direct form linear prediction filtering
- Normal equations for linear prediction filtering
- Levinson algorithm
- Linear prediction lattice filtering
Unit 3 Digital Wiener Filtering
- Wiener smoothing and prediction filters
- Application of Wiener smoothing to noise cancelling
- Application of Wiener prediction filters
- linear MMSE filtering
- Minimum variance beam forming
Unit 4 Least Mean Squares Adaptive Filter
- Fundamentals of adaptive systems
- LMS adaptive algorithm
- Properties of LMS adaptive filter
- Least squares adaptive filters
- frequency domain adaptive filters
- Adaptive lattice filters
- Godard algorithm
Unit 5 Normalizes Least Mean Square Filters (NLMS), Recursive Least
- Square based (RLS) based filters
- RLS(Recursive least squares)
- Generalisations of LMS and RLS
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