Detection and Estimation Theory
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Follow on Instagram for UpdatesDetection and Estimation Theory Syllabus — Unit-wise Content
The official GTU curriculum for Detection and Estimation Theory (subject code 3724116) as prescribed for EAC( · Semester 2 divides the course into 6 units, covering 30 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 (3724116)Unit 1 Review of Vector Spaces
- Vectors and matrices: notation and properties
- orthogonality and linear independence
- distance properties
- matrix operations
- Eigen values and eigenvectors
Unit 2 Properties of Symmetric Matrices
- Diagonalization of symmetric matrices
- symmetric positive definite and semi definite matrices
- principal component analysis (PCA)
- singular value decomposition
Unit 3 Stochastic Processes
- Time average and moments
- power spectral density
- covariance matrices
- response of LTI system to random process
- cyclo-stationary process, and spectral factorization
Unit 4 Detection Theory
- Detection in white Gaussian noise
- correlator and matched filter interpretation
- Bayes‘ criterion of signal detection, MAP, LMS, entropy detectors
- detection in colored Gaussian noise
- Karhunen-Loeve expansions and whitening filters
Unit 5 Estimation Theory
- Minimum variance estimators
- Cramer-Rao lower bound
- examples of linear models
- system identification
- Markov classification
- clustering algorithms
Unit 6 Topics in Kalman and Weiner Filtering
- Discrete time Wiener-Hopf equation
- error variance computation
- causal discrete time Wiener filter
- discrete Kalman filter
- extended 8 Subject Code: 3724116 w.e.f
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