Media Storage Type : 64 GB USB Stick (2 Nos), 32 GB USB Stick (1 No.)
NPTEL Subject Matter Expert : Dr. Arun K.Tangirala
NPTEL Co-ordinating Institute : IIT Madras
NPTEL Lecture Count : 121
NPTEL Course Size : 149 GB
NPTEL PDF Text Transcription : Available and Included
NPTEL Subtitle Transcription : Available and Included (SRT)
Lecture Titles:
Lecture 1 - Motivation and Overview 1
Lecture 2 - Motivation and Overview 2
Lecture 3 - Motivation and Overview 3
Lecture 4 - Motivation and Overview 4
Lecture 5 - Journey into Identification 1
Lecture 6 - Journey into Identification 2
Lecture 7 - Journey into Identification 3
Lecture 8 - Journey into Identification (Case Studies) 4
Lecture 9 - Journey into Identification (Case Studies) 5
Lecture 10 - Journey into Identification (Case Studies) 6
Lecture 11 - Journey into Identification (Case Studies) 7
Lecture 12 - Journey into Identification (Case Studies) 8
Lecture 13 - Journey into Identification (Case Studies) 9
Lecture 14 - Journey into Identification (Case Studies) 10
Lecture 15 - Journey into Identification (Case Studies) 11
Lecture 16 - Journey into Identification (Case Studies) 12
Lecture 17 - Journey into Identification (Case Studies) 13
Lecture 18 - Journey into Identification (Case Studies) 14
Lecture 19 - Journey into Identification (Case Studies) 15
Lecture 20 - Journey into Identification (Case Studies) 16
Lecture 21 - Journey into Identification 17
Lecture 22 - Journey into Identification 18
Lecture 23 - Response-based Description 1
Lecture 24 - Response-based Description 2
Lecture 25 - Response-based Description 3
Lecture 26 - Response-based Description 4
Lecture 27 - Response-based Description 5
Lecture 28 - Response-based Description 6
Lecture 29 - Response-based Description 7
Lecture 30 - Response-based Description 8
Lecture 31 - Response-based Description 9
Lecture 32 - Response-based Description 10
Lecture 33 - Response-based Description 11
Lecture 34 - Response-based Description 12
Lecture 35 - Response-based Description 13
Lecture 36 - Discrete time LTI system 1
Lecture 37 - Discrete time LTI system 2
Lecture 38 - z-Domain Descriptions 1
Lecture 39 - z-Domain Descriptions 2
Lecture 40 - z-Domain Descriptions 3
Lecture 41 - z-Domain Descriptions 4
Lecture 42 - z-Domain Descriptions 5
Lecture 43 - z-Domain Descriptions 6
Lecture 44 - State Space Representation 1
Lecture 45 - State Space Representation 2
Lecture 46 - State Space Representation 3
Lecture 47 - State Space Representation 4
Lecture 48 - Sampled - Data Systems 1
Lecture 49 - Sampled - Data Systems 2
Lecture 50 - Sampled - Data Systems 3
Lecture 51 - Sampled - Data Systems 4
Lecture 52 - Sampled - Data Systems 5
Lecture 53 - Sampled - Data Systems 6
Lecture 54 - Sampled - Data Systems 7
Lecture 55 - Sampled - Data Systems 8
Lecture 56 - Probability_Random variables and moments - Review 1
Lecture 57 - Probability_Random variables and moments - Review 2
Lecture 58 - Probability_Random variables and moments - Review 3
Lecture 59 - Probability_Random variables and moments - Review 4
Lecture 60 - Probability_Random variables and moments - Review 5
Lecture 61 - Probability_Random variables and moments - Review 6
Lecture 62 - Random Processes - Review 1
Lecture 63 - Random Processes - Review 2
Lecture 64 - Random Processes - Review 3
Lecture 65 - Random Processes - Review 4
Lecture 66 - Random Processes - Review 5
Lecture 67 - Random Processes - Review 6 (MATLAB)
Lecture 68 - Random Processes - Review 7
Lecture 69 - Random Processes - Review 8
Lecture 70 - Spectral Representation 1
Lecture 71 - Spectral Representation 2
Lecture 72 - Spectral Representation 3
Lecture 73 - Models for Identification 1
Lecture 74 - Models for Identification 2
Lecture 75 - Models for Identification 3
Lecture 76 - Models for Identification 4
Lecture 77 - One step and multi-step ahead prediction 1
Lecture 78 - One step and multi-step ahead prediction 2
Lecture 79 - One step and multi-step ahead prediction 3
Lecture 80 - One step and multi-step ahead prediction 4
Lecture 81 - One step and multi-step ahead prediction 5
Lecture 82 - Introduction to estimation theory 1
Lecture 83 - Introduction to estimation theory 2
Lecture 84 - Fisher's information and properties of estimators 1
Lecture 85 - Fisher's information and properties of estimators 2
Lecture 86 - Fisher's information and properties of estimators 3
Lecture 87 - Fisher's information and properties of estimators 4
Lecture 88 - Fisher's information and properties of estimators 5
Lecture 89 - Fisher's information and properties of estimators 6
Lecture 90 - Fisher's information and properties of estimators 7
Lecture 91 - Fisher's information and properties of estimators 8
Lecture 92 - Fisher's information and properties of estimators 9
Lecture 93 - Fisher's information and properties of estimators 10
Lecture 94 - Fisher's information and properties of estimators 11
Lecture 95 - Fisher's information and properties of estimators 12
Lecture 96 - Fisher's information and properties of estimators 13
Lecture 97 - Fisher's information and properties of estimators 14
Lecture 98 - Fisher's information and properties of estimators 15
Lecture 99 - Estimation of non-parametric model 1
Lecture 100 - Estimation of non-parametric model 2
Lecture 101 - Estimation of non-parametric model 3
Lecture 102 - Estimation of non-parametric model 4
Lecture 103 - Estimation of non-parametric model 5
Lecture 104 - Estimation of non-parametric model 3
Lecture 105 - Estimation of non-parametric model 4
Lecture 106 - Estimation of non-parametric model 5
Lecture 107 - Estimation of parametric model 1
Lecture 108 - Estimation of parametric model 2
Lecture 109 - Estimation of parametric model 3
Lecture 110 - Estimation of parametric model 4
Lecture 111 - State-Space/Subspace identification 1
Lecture 112 - State-Space/Subspace identification 2
Lecture 113 - State-Space/Subspace identification 3
Lecture 114 - State-Space/Subspace identification 4
Lecture 115 - State-Space/Subspace identification 5
Lecture 116 - State-Space/Subspace identification 6
Lecture 117 - State-Space/Subspace identification 7
Lecture 118 - State-Space/Subspace identification 8
Lecture 119 - Input for Identification
Lecture 120 - Input for Identification
Lecture 121 - Input for Identification