# Statistical Signal Processing

- Institution: IIT Guwahati
- Department: Electrical Engineering
- Teacher: Prof. Prabin Kumar Bora
- Level: Undergraduate
- Language: English
- Subjects: Engineering
- Source: [NPTEL](https://nptel.ac.in/courses/108103158)
- Licence: [CC BY-NC-SA](https://nptel.ac.in/faq) (Non-commercial use only.)
- Syllabus: [at the source](https://nptel.ac.in/courses/108103158)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

## Lectures

1. [Lec 1 : Overview of Statistical Signal Processing](https://invisiblenetwork.ai/learn/nptel/108103158/98468d27bca1) (Video)
2. [Lec 2 : Probability and Random Variables](https://invisiblenetwork.ai/learn/nptel/108103158/e396eb6b56f5) (Video)
3. [Lec 3 : Linear Algebra of Random Variables](https://invisiblenetwork.ai/learn/nptel/108103158/d451b73266a5) (Video)
4. [Lec 4 : Random Processes](https://invisiblenetwork.ai/learn/nptel/108103158/04b04afe21e6) (Video)
5. [Lec 5 : Linear Shift Invariant Systems with Random Inputs](https://invisiblenetwork.ai/learn/nptel/108103158/5ece32eb6e1a) (Video)
6. [Lec 6 : White Noise and Spectral Factorization Theorem](https://invisiblenetwork.ai/learn/nptel/108103158/8c214dedb392) (Video)
7. [Lec 7 : Linear Models of Random Signals](https://invisiblenetwork.ai/learn/nptel/108103158/d35c36da0975) (Video)
8. [Lec 8 : Estimation Theory 1](https://invisiblenetwork.ai/learn/nptel/108103158/ac625f712501) (Video)
9. [Lec 9 : Estimation Theory 2: MVUE and Cramer Rao Lower Bound](https://invisiblenetwork.ai/learn/nptel/108103158/198e7aff0a6e) (Video)
10. [Lec 10 : Cramer Rao Lower Bound 2](https://invisiblenetwork.ai/learn/nptel/108103158/7160a3096d9a) (Video)
11. [Lec 11 : MVUE through Sufficient Statistic](https://invisiblenetwork.ai/learn/nptel/108103158/7494d35a2d09) (Video)
12. [Lec 12 : MVUE through Sufficient Statistic 2](https://invisiblenetwork.ai/learn/nptel/108103158/f08b7c047492) (Video)
13. [Lec 13 : Method of Moments and Maximum Likelihood Estimators](https://invisiblenetwork.ai/learn/nptel/108103158/c5650b0ca85a) (Video)
14. [Lec 14 : Properties of Maximum Likelihood Estimator (MLE)](https://invisiblenetwork.ai/learn/nptel/108103158/f1c0c6ed26be) (Video)
15. [Lec 15 : Bayesian Estimators](https://invisiblenetwork.ai/learn/nptel/108103158/192523369dcf) (Video)
16. [Lec 16 : Bayesian Estimators 2](https://invisiblenetwork.ai/learn/nptel/108103158/e7d3dad8926d) (Video)
17. [Lec 17 : Optimal linear filters: Wiener Filter](https://invisiblenetwork.ai/learn/nptel/108103158/e42bb249e831) (Video)
18. [Lec 18 : FIR Wiener filter](https://invisiblenetwork.ai/learn/nptel/108103158/c0ee59cda55e) (Video)
19. [Lec 19 : Non-Causual IIR Wiener Filter](https://invisiblenetwork.ai/learn/nptel/108103158/036c049e1d68) (Video)
20. [Lec 20 : Causal IIR Wiener Filter](https://invisiblenetwork.ai/learn/nptel/108103158/e9a7351a7e09) (Video)
21. [Lec 21: Linear Prediction of Signals 1](https://invisiblenetwork.ai/learn/nptel/108103158/960815bfa02f) (Video)
22. [Lec 22 : Linear Prediction of Signals 2](https://invisiblenetwork.ai/learn/nptel/108103158/e2cdd06755f8) (Video)
23. [Lec 23 : Linear Prediction of Signals 3](https://invisiblenetwork.ai/learn/nptel/108103158/0f3a6768f64c) (Video)
24. [Lec 24: Review Assignment 1](https://invisiblenetwork.ai/learn/nptel/108103158/f9ffcd1dca14) (Video)
25. [Lec 25: Adaptive Filters 1](https://invisiblenetwork.ai/learn/nptel/108103158/4938785404ad) (Video)
26. [Lec 26: Adaptive Filters 2](https://invisiblenetwork.ai/learn/nptel/108103158/ab5252e565a7) (Video)
27. [Lec 27: Adaptive Filters 3](https://invisiblenetwork.ai/learn/nptel/108103158/d25d59b72eb1) (Video)
28. [Lec 28: Review Assignment 2](https://invisiblenetwork.ai/learn/nptel/108103158/2dcf5c42c6f2) (Video)
29. [Lec 29: Adaptive Filters 4](https://invisiblenetwork.ai/learn/nptel/108103158/295fc357d270) (Video)
30. [Lec 30: Adaptive Filters 4(cont.)](https://invisiblenetwork.ai/learn/nptel/108103158/cecf983187f2) (Video)
31. [Lec 31: Review Assignment 3](https://invisiblenetwork.ai/learn/nptel/108103158/4fdff30b7069) (Video)
32. [Lec 32: Recursive Least Squares (RLS) Adaptive Filter](https://invisiblenetwork.ai/learn/nptel/108103158/3017ef578582) (Video)
33. [Lec 33: Recursive Least Squares (RLS) Adaptive Filter - 2](https://invisiblenetwork.ai/learn/nptel/108103158/29b730742955) (Video)
34. [Lec 34: Review Assignment 4](https://invisiblenetwork.ai/learn/nptel/108103158/734275940d0a) (Video)
35. [Lec 35: Kalman Filter - 1](https://invisiblenetwork.ai/learn/nptel/108103158/9e8358ddec97) (Video)
36. [Lec 36: Vector Kalman Filter](https://invisiblenetwork.ai/learn/nptel/108103158/fd39d36ff8c8) (Video)
37. [Lec 37: Linear Models of Random Signals](https://invisiblenetwork.ai/learn/nptel/108103158/037e375e8e9f) (Video)
38. [Lec 38: Review - 1](https://invisiblenetwork.ai/learn/nptel/108103158/f0ffa09f9f79) (Video)
39. [Lec 39: Review - 2](https://invisiblenetwork.ai/learn/nptel/108103158/eb691c02a08a) (Video)
40. [Live Session 09-02-2021](https://invisiblenetwork.ai/learn/nptel/108103158/98468d27bca1-2) (Video)
41. [Live Session 06-05-2020](https://invisiblenetwork.ai/learn/nptel/108103158/e396eb6b56f5-2) (Video)