| Course Name | Detection And Estimation Theory |
| Course Code | 25MA733 |
| Program | M.Tech. Wireless Networks & Applications (Specialising in IoT, AI, 5G, Blockchain) (For Working Professionals & Regular Students) |
| Credits | 3 |
| Campus | Amritapuri |
Sufficiency, Exponential families, Methods of estimation: Least Squares, Maximum likelihood, method of moments, Bayes; Algorithms for estimation. Performance: Bayes, minimax, unbiasedness, Cramer-Rao inequality, Rao-Blackwell Theorem; Asymptotic Performance: Consistency, Asymptotic normality, Asymptotic optimality, Hypothesis Testing Neyman-Pearson Lemma, UMP Tests, Monotone likelihood ratio, Generalized likelihood ratio test, confidence bounds.
Course Outcome Statement (CO)
|
CO1 |
Understand the basic concepts of signal detection and estimation |
|
CO2 |
Understand different hypotheses in detection and estimation problems |
|
CO3 |
Understand the conceptual basics of detection and estimation of signals in white and non-white Gaussian noise |
|
CO4 |
Understand the detection of random signals and the time varying waveform detection and its estimation |
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