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Sl.No Chapter Name MP4 Download
1Lec 01- Vectors and Matrices- Linear Independence and Rank Download
2Lec 02 - Eigenvectors and Eigenvalues of Matrices and their PropertiesDownload
3Lec 03 - Positive Semidefinite (PSD) and Postive Definite (PD) Matrices and their Properties Download
4Lec 04 - Inner Product Space and it's Properties: Linearity, Symmetry and Positive Semi-definiteDownload
5Lec 05 - Inner Product Space and its Properties: Cauchy Schwarz InequalityDownload
6Lec 06 - Properties of Norm, Gaussian Elimination and Echleon form of matrix Download
7Lec 07- Gram Schmidt Orthogonalization Procedure Download
8Lec 08- Null Space and Trace of Matrices Download
9Lec 09- Eigenvalue Decomposition of Hermitian Matrices and Properties Download
10Lec 10- Matrix Inversion Lemma (Woodbury identity) Download
11Lec 11- Introduction to Convex Sets and Properties Download
12Lec 12- Affine Set Examples and Application Download
13Lec 13- Norm Ball and its Practical Applications Download
14Lec 14- Ellipsoid and its Practical Applications Download
15Lec 15- Norm Cone,Polyhedron and its Applications Download
16Lec 16- Applications: Cooperative Cellular TransmissionDownload
17Lec 17- Positive Semi Definite Cone And Positive Semi Definite (PSD) Matrices Download
18Lec 18-Introduction to Affine functions and examplesDownload
19Lecture 19-norm balls and Matrix properties:Trace,DeterminantDownload
20Lecture 20-Inverse of a Positive Definite MatrixDownload
21Lecture 21-Example Problems: Property of Norms,Problems on Convex SetsDownload
22Lecture 22-Problems on Convex Sets(contd.)Download
23Lecture 23-Introduction to Convex and Concave FunctionsDownload
24Lecture 24-Properties of Convex Functions with examplesDownload
25Lec 25-Test for Convexity: Positive Semidefinite Hessian Matrix Download
26Lec 26-Application: MIMO Receiver Design as a Least Squares Problem Download
27Lec 27-Jensen's Inequality and Practical Application Download
28Lec 28-Jensen's Inequality application Download
29Lec 29 - Properties of Convex Functions Download
30Lec 30 - Conjugate Function and Examples to prove Convexity of various Functions Download
31Lec 31- Example problems: Operations preserving Convexity(log-sum, average) and Quasi Convexity Download
32Lec 32-Example Problems: Verify Convexity, Quasi -Convexity and Quasi- Concavity of functions Download
33Lec 33-Example Problems:Perspective function, Product of Convex functions and Pointwise Maximum is Convex Download
34Lec 34- Practical Application: Beamforming in Multi-antenna Wireless CommunicationDownload
35Lec 35 - Practical Application: Maximal Ratio Combiner for Wireless Systems Download
36Lec 36- Practical Application: Multi-antenna Beamforming with Interfering User Download
37Lec 37- Practical Application: Zero-Forcing (ZF) Beamforming with Interfering User Download
38Lec 38- Practical Application: Robust Beamforming With Channel Uncertainity for Wireless Systems Download
39Lec 39- Practical Application: Robust Beamformer Design for Wireless Systems Download
40Lec 40 - Practical Application: Detailed Solution for Robust Beamformer Computation in Wireless Systems TextDownload
41Lec 41- Linear modeling and Approximation Problems: Least Squares Download
42Lec 42-Geometric Intuition for Least Squares Download
43Lec 43- Practical Application: Multi antenna channel estimation Download
44Lec 44- Practical Application:Image deblurring Download
45Lec 45- Least Norm Signal Estimation Download
46Lec 46- Regularization: Least Squares + Least Norm Download
47Lec 47- Convex Optimization Problem representation: Canonical form, Epigraph form Download
48Lec 48-Linear Program Practical Application: Base Station Co-operation Download
49Lec 49- Stochastic Linear Program,Gaussian Uncertainty Download
50Lec 50- Practical Application: Multiple Input Multiple Output (MIMO) BeamformingDownload
51Lec 51- Practical Application: Multiple Input Multiple Output (MIMO) Beamformer Design Download
52Lec 52-Practical Application: Co-operative Communication, Overview and various Protocols used Download
53Lec 53- Practical Application: Probability of Error Computation for Co-operative Communication Download
54Lec 54- Practical Application:Optimal power allocation factor determination for Co-operative Communication Download
55Lec 55- Practical Application: Compressive Sensing Download
56Lec 56- Practical Application Download
57Lec 57- Practical Application- Orthogonal Matching Pursuit (OMP) algorithm for Compressive Sensing Download
58Lec 58- Example Problem: Orthogonal Matching Pursuit (OMP) algorithm Download
59Lec 59- Practical Application : L1 norm minimization and regularization approach for Compressive Sensing Optimization problem Download
60Lec 60- Practical Application of Machine Learning and Artificial Intelligence:Linear Classification, Overview and Motivation Download
61Lec 61- Practical Application: Linear Classifier (Support Vector Machine) Design Download
62Lec 62- Practical Application: Approximate Classifier Design Download
63Lec 63- Concept of Duality Download
64Lec 64-Relation between optimal value of Primal & Dual Problems, concepts of Duality gap and Strong Duality Download
65Lec 65-Example problem on Strong Duality Download
66Lec 66- Karush-Kuhn-Tucker(KKT) conditions Download
67Lec 67- Application of KKT condition:Optimal MIMO power allocation(Waterfilling) Download
68Lec 68- Optimal MIMO Power allocation(Waterfilling)-II Download
69Lec 69- Example problem on Optimal MIMO Power allocation(Waterfilling) Download
70Lec 70- Linear objective with box constraints, Linear ProgrammingDownload
71Lec 71- Example Problems IIDownload
72Lec 72- Examples on Quadratic Optimization Download
73Lec 73- Examples on Duality: Dual Norm, Dual of Linear Program(LP) Download
74Lec 74- Examples on Duality: Min-Max problem, Analytic Centering Download
75Lec 75- Semi Definite Program(SDP) and its application:MIMO symbol vector decoding Download
76Lec 76- Application:SDP for MIMO Maximum Likelihood(ML) Detection Download
77Lec 77- Introduction to big Data: Online Recommender System(Netflix)Download
78Lec 78- Matrix Completion Problem in Big Data: Netflix-I Download
79Lec 79- Matrix Completion Problem in Big Data: Netflix-II Download

Sl.No Chapter Name English
1Lec 01- Vectors and Matrices- Linear Independence and Rank Download
Verified
2Lec 02 - Eigenvectors and Eigenvalues of Matrices and their PropertiesDownload
Verified
3Lec 03 - Positive Semidefinite (PSD) and Postive Definite (PD) Matrices and their Properties Download
Verified
4Lec 04 - Inner Product Space and it's Properties: Linearity, Symmetry and Positive Semi-definiteDownload
Verified
5Lec 05 - Inner Product Space and its Properties: Cauchy Schwarz InequalityDownload
Verified
6Lec 06 - Properties of Norm, Gaussian Elimination and Echleon form of matrix Download
Verified
7Lec 07- Gram Schmidt Orthogonalization Procedure Download
Verified
8Lec 08- Null Space and Trace of Matrices Download
Verified
9Lec 09- Eigenvalue Decomposition of Hermitian Matrices and Properties Download
Verified
10Lec 10- Matrix Inversion Lemma (Woodbury identity) Download
Verified
11Lec 11- Introduction to Convex Sets and Properties Download
Verified
12Lec 12- Affine Set Examples and Application Download
Verified
13Lec 13- Norm Ball and its Practical Applications Download
Verified
14Lec 14- Ellipsoid and its Practical Applications Download
Verified
15Lec 15- Norm Cone,Polyhedron and its Applications Download
Verified
16Lec 16- Applications: Cooperative Cellular TransmissionDownload
Verified
17Lec 17- Positive Semi Definite Cone And Positive Semi Definite (PSD) Matrices Download
Verified
18Lec 18-Introduction to Affine functions and examplesDownload
Verified
19Lecture 19-norm balls and Matrix properties:Trace,DeterminantDownload
Verified
20Lecture 20-Inverse of a Positive Definite MatrixDownload
Verified
21Lecture 21-Example Problems: Property of Norms,Problems on Convex SetsDownload
Verified
22Lecture 22-Problems on Convex Sets(contd.)Download
Verified
23Lecture 23-Introduction to Convex and Concave FunctionsDownload
Verified
24Lecture 24-Properties of Convex Functions with examplesDownload
Verified
25Lec 25-Test for Convexity: Positive Semidefinite Hessian Matrix Download
Verified
26Lec 26-Application: MIMO Receiver Design as a Least Squares Problem Download
Verified
27Lec 27-Jensen's Inequality and Practical Application Download
Verified
28Lec 28-Jensen's Inequality application Download
Verified
29Lec 29 - Properties of Convex Functions Download
Verified
30Lec 30 - Conjugate Function and Examples to prove Convexity of various Functions Download
Verified
31Lec 31- Example problems: Operations preserving Convexity(log-sum, average) and Quasi Convexity Download
Verified
32Lec 32-Example Problems: Verify Convexity, Quasi -Convexity and Quasi- Concavity of functions Download
Verified
33Lec 33-Example Problems:Perspective function, Product of Convex functions and Pointwise Maximum is Convex Download
Verified
34Lec 34- Practical Application: Beamforming in Multi-antenna Wireless CommunicationDownload
Verified
35Lec 35 - Practical Application: Maximal Ratio Combiner for Wireless Systems Download
Verified
36Lec 36- Practical Application: Multi-antenna Beamforming with Interfering User Download
Verified
37Lec 37- Practical Application: Zero-Forcing (ZF) Beamforming with Interfering User Download
Verified
38Lec 38- Practical Application: Robust Beamforming With Channel Uncertainity for Wireless Systems Download
Verified
39Lec 39- Practical Application: Robust Beamformer Design for Wireless Systems Download
Verified
40Lec 40 - Practical Application: Detailed Solution for Robust Beamformer Computation in Wireless Systems TextDownload
Verified
41Lec 41- Linear modeling and Approximation Problems: Least Squares Download
Verified
42Lec 42-Geometric Intuition for Least Squares Download
Verified
43Lec 43- Practical Application: Multi antenna channel estimation Download
Verified
44Lec 44- Practical Application:Image deblurring Download
Verified
45Lec 45- Least Norm Signal Estimation Download
Verified
46Lec 46- Regularization: Least Squares + Least Norm Download
Verified
47Lec 47- Convex Optimization Problem representation: Canonical form, Epigraph form Download
Verified
48Lec 48-Linear Program Practical Application: Base Station Co-operation Download
Verified
49Lec 49- Stochastic Linear Program,Gaussian Uncertainty Download
Verified
50Lec 50- Practical Application: Multiple Input Multiple Output (MIMO) BeamformingDownload
Verified
51Lec 51- Practical Application: Multiple Input Multiple Output (MIMO) Beamformer Design Download
Verified
52Lec 52-Practical Application: Co-operative Communication, Overview and various Protocols used Download
Verified
53Lec 53- Practical Application: Probability of Error Computation for Co-operative Communication Download
Verified
54Lec 54- Practical Application:Optimal power allocation factor determination for Co-operative Communication Download
Verified
55Lec 55- Practical Application: Compressive Sensing Download
Verified
56Lec 56- Practical Application Download
Verified
57Lec 57- Practical Application- Orthogonal Matching Pursuit (OMP) algorithm for Compressive Sensing Download
Verified
58Lec 58- Example Problem: Orthogonal Matching Pursuit (OMP) algorithm Download
Verified
59Lec 59- Practical Application : L1 norm minimization and regularization approach for Compressive Sensing Optimization problem Download
Verified
60Lec 60- Practical Application of Machine Learning and Artificial Intelligence:Linear Classification, Overview and Motivation Download
Verified
61Lec 61- Practical Application: Linear Classifier (Support Vector Machine) Design Download
Verified
62Lec 62- Practical Application: Approximate Classifier Design Download
Verified
63Lec 63- Concept of Duality Download
Verified
64Lec 64-Relation between optimal value of Primal & Dual Problems, concepts of Duality gap and Strong Duality Download
Verified
65Lec 65-Example problem on Strong Duality Download
Verified
66Lec 66- Karush-Kuhn-Tucker(KKT) conditions Download
Verified
67Lec 67- Application of KKT condition:Optimal MIMO power allocation(Waterfilling) Download
Verified
68Lec 68- Optimal MIMO Power allocation(Waterfilling)-II Download
Verified
69Lec 69- Example problem on Optimal MIMO Power allocation(Waterfilling) Download
Verified
70Lec 70- Linear objective with box constraints, Linear ProgrammingDownload
Verified
71Lec 71- Example Problems IIDownload
Verified
72Lec 72- Examples on Quadratic Optimization Download
Verified
73Lec 73- Examples on Duality: Dual Norm, Dual of Linear Program(LP) Download
Verified
74Lec 74- Examples on Duality: Min-Max problem, Analytic Centering Download
Verified
75Lec 75- Semi Definite Program(SDP) and its application:MIMO symbol vector decoding Download
Verified
76Lec 76- Application:SDP for MIMO Maximum Likelihood(ML) Detection Download
Verified
77Lec 77- Introduction to big Data: Online Recommender System(Netflix)Download
Verified
78Lec 78- Matrix Completion Problem in Big Data: Netflix-I Download
Verified
79Lec 79- Matrix Completion Problem in Big Data: Netflix-II Download
Verified


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