Lecture 01_Part 1 – Motivation and Overview 1

Lecture 01_Part 2 – Motivation and Overview 2

Lecture 02_Part 1 – Motivation and Overview 3

Lecture 02_Part 2 – Motivation and Overview 4

Lecture 03_Part 1 – Journey into Identification 1

Lecture 03_Part 2 – Journey into Identification 2

Lecture 03_Part 2 – Journey into Identification 2

Lecture 04_Part 1 – Journey into Identification 3

Lecture 04_Part 2 – Journey into Identification (Case Studies) 4

Lecture 04_Part 3 – Journey into Identification (Case Studies) 5

Lecture 05_Part 1 – Journey into Identification (Case Studies) 6

Lecture 05_Part 3 – Journey into Identification (Case Studies) 8

Lecture 06_Part 1 – Journey into Identification (Case Studies) 9

Lecture 06_Part 2 – Journey into Identification (Case Studies) 10

Lecture 07_Part 1 – Journey into Identification (Case Studies) 11

Lecture 07_Part 2 – Journey into Identification (Case Studies) 12

Lecture 07_Part 3 – Journey into Identification (Case Studies) 13

Lecture 08_Part 1 – Journey into Identification (Case Studies) 14

Lecture 08_Part 2 – Journey into Identification (Case Studies) 15

Lecture 09_Part 1 – Journey into Identification (Case Studies) 16

Lecture 09_Part 2 – Journey into Identification 17

Lecture 10_Part 1 – Journey into Identification 18

Lecture 10_Part 2 – Response-based Description 1

Lecture 10_Part 3 – Response-based Description 2

Lecture 11_Part 1 – Response-based Description 3

Lecture 11_Part 2 – Response-based Description 4

Lecture 12_Part 1 – Response-based Description 5

Lecture 12_Part 2 – Response-based Description 6

Lecture 12_Part 3 – Response-based Description 7

Lecture 13_Part 1 – Response-based Description 8

Lecture 13_Part 2 – Response-based Description 9

Lecture 14_Part 1 – Response-based Description 10

Lecture 14_Part 2 – Response-based Description 11

Lecture 14_Part 3 – Response-based Description 12

Lecture 15_Part 1 – Response-based Description 13

Lecture 15_Part 2 – Discrete time LTI system 1

Lecture 16_Part 1 – Discrete time LTI system 2

Lecture 16_Part 2 – z-Domain Descriptions 1

Lecture 17_Part 1 – z-Domain Descriptions 2

Lecture 17_Part 2 – z-Domain Descriptions 3

Lecture 18_Part 1 – z-Domain Descriptions 4

Lecture 18_Part 2 – z-Domain Descriptions 5

Lecture 18_Part 3 – z-Domain Descriptions 6

Lecture 19_Part 1 – State Space Representation 1

Lecture 19_Part 2 – State Space Representation 2

Lecture 20_Part 1 – State Space Representation 3

Lecture 20_Part 2 – State Space Representation 4

Lecture 21_Part 1 – Sampled - Data Systems 1

Lecture 21_Part 2 – Sampled - Data Systems 2

Lecture 22_Part 1 – Sampled - Data Systems 3

Lecture 22_Part 2 – Sampled - Data Systems 4

Lecture 23_Part 1 – Sampled - Data Systems 5

Lecture 23_Part 2 – Sampled - Data Systems 6

Lecture 24_Part 1 – Sampled - Data Systems 7

Lecture 24_Part 2 – Sampled - Data Systems 8

Lecture 25_Part 1 – Probability_Random variables and moments - Review 1

Lecture 25_Part 2 – Probability_Random variables and moments - Review 2

Lecture 26_Part 1 – Probability_Random variables and moments - Review 3

Lecture 26_Part 2 – Probability_Random variables and moments - Review 4

Lecture 27_Part 1 – Probability_Random variables and moments - Review 5

Lecture 27_Part 2 – Probability_Random variables and moments - Review 6

Lecture 28_Part 1 – Random Processes - Review 1

Lecture 28_Part 2 – Random Processes - Review 2

Lecture 29_Part 1 – Random Processes - Review 3

Lecture 29_Part 2 – Random Processes - Review 4

Lecture 30_Part 1 – Random Processes - Review 5

Lecture 30_Part 2 – Random Processes - Review – (MATLAB) 6

Lecture 31_Part 1 – Random Processes - Review 7

Lecture 31_Part 2 – Random Processes - Review 8

Lecture 32_Part 1 – Spectral Representation 1

Lecture 32_Part 2A – Spectral Representation 2

Lecture 32_Part 2B – Spectral Representation 3

Lecture 33_Part 1 – Models for Identification 1

Lecture 33_Part 2 – Models for Identification 2

Lecture 34_Part 1 – Models for Identification 3

Lecture 34_Part 2 – Models for Identification 4

Lecture 35_Part 1 – One step and multi-step ahead prediction 1

Lecture 35_Part 2 – One step and multi-step ahead prediction 2

Lecture 36_Part 1 – One step and multi-step ahead prediction 3

Lecture 36_Part 2 – One step and multi-step ahead prediction 4

Lecture 36_Part 3 – One step and multi-step ahead prediction 5

Lecture 37_Part 1 – Introduction to estimation theory 1

Lecture 37_Part 2 – Introduction to estimation theory 2

Lecture 38_Part 1 – Fisher’s information and properties of estimators 1

Lecture 38_Part 2 – Fisher’s information and properties of estimators 2

Lecture 39_Part 1 – Fisher’s information and properties of estimators 3

Lecture 39_Part 2 – Fisher’s information and properties of estimators 4

Lecture 40_Part 1 – Fisher’s information and properties of estimators 5

Lecture 40_Part 2 – Fisher’s information and properties of estimators 6

Lecture 41_Part 1 – Fisher’s information and properties of estimators 7

Lecture 41_Part 2 – Fisher’s information and properties of estimators 8

Lecture 42_Part 1 – Fisher’s information and properties of estimators 9

Lecture 43_Part 1 – Fisher’s information and properties of estimators 11

Lecture 43_Part 2 – Fisher’s information and properties of estimators 12

Lecture 43_Part 3 – Fisher’s information and properties of estimators 13

Lecture 43_Part 4 – Fisher’s information and properties of estimators 14

Lecture 44_Part 1 – Fisher’s information and properties of estimators 15

Lecture 45_Part 1 – Estimation of non-parametric model 1

Lecture 45_Part 2 – Estimation of non-parametric model 2

Lecture 46_Part 1 – Estimation of non-parametric model 3

Lecture 46_Part 2 – Estimation of non-parametric model 4

Lecture 47_Part 2 – Estimation of non-parametric model 4

Lecture 47_Part 3 – Estimation of non-parametric model 5

Lecture 48_Part 1 – Estimation of parametric model 1

Lecture 48_Part 2 – Estimation of parametric model 2

Lecture 48_Part 3 – Estimation of parametric model 3

Lecture 49_Part 1 – Estimation of parametric model 4

Lecture 49_Part 2 – State-Space/Subspace identification 1

Lecture 50_Part 1 – State-Space/Subspace identification 2

Lecture 50_Part 2 – State-Space/Subspace identification 3

Lecture 51_Part 1 – State-Space/Subspace identification 4

Lecture 51_Part 2 – State-Space/Subspace identification 5

Lecture 51_Part 3 – State-Space/Subspace identification 6

Lecture 51_Part 4 – State-Space/Subspace identification 7

Lecture 51_Part 5 – State-Space/Subspace identification 8

Lecture 52_Part 1 – Input for Identification

Lecture 52_Part 2 – Input for Identification

Lecture 52_Part 3 – Input for Identification