Lec-24 Linear Regression-Recursive Least Squares | Courses.com

Course Lectures

Lec-1 Introduction
Prof. S. Mukhopadhyay

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Lec-2 Probability Theory
Prof. S. Mukhopadhyay

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Lec-3 Random Variables
Prof. S. Mukhopadhyay

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Lec-4 Function of Random Variable Joint Density
Prof. S. Mukhopadhyay

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Lec-5 Mean and Variance
Prof. S. Mukhopadhyay

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Lec-6 Random Vectors Random Processes
Prof. S. Mukhopadhyay

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Lec-7 Random Processes and Linear Systems
Prof. S. Mukhopadhyay

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Lec-8 Some Numerical Problems
Prof. S. Mukhopadhyay

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Lec-9 Miscellaneous Topics on Random Process
Prof. S. Mukhopadhyay

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Lec-10 Linear Signal Models
Prof. S. Mukhopadhyay

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Lec-11 Linear Mean Sq.Error Estimation
Prof. S. Mukhopadhyay

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Lec-12 Auto Correlation and Power Spectrum Estimation
Prof. S. Mukhopadhyay

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lec-13 Z-Transform Revisited Eigen Vectors/Values
Prof. S. Mukhopadhyay

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Lec-14 The Concept of Innovation
Prof. S. Mukhopadhyay

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Lec-15 Last Squares Estimation Optimal IIR Filters
Prof. S. Mukhopadhyay

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Lec-16 Introduction to Adaptive FIlters
Prof. S. Mukhopadhyay

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Lec-17 State Estimation
Prof. S. Mukhopadhyay

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Lec-18 Kalman Filter-Model and Derivation
Prof. S. Mukhopadhyay

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Lec-19 Kalman Filter-Derivation(Contd...)
Prof. S. Mukhopadhyay

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Lec-20 Estimator Properties
Prof. S. Mukhopadhyay

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Lec-21 The Time-Invariant Kalman Filter
Prof. S. Mukhopadhyay

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Lec-22 Kalman Filter-Case Study
Prof. S. Mukhopadhyay

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Lec-24 Linear Regression-Recursive Least Squares
Prof. S. Mukhopadhyay

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Lec-25 Variants of LSE
Prof. S. Mukhopadhyay

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Lec-26 Least Square Estimation
Prof. S. Mukhopadhyay

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Lec-27 Model Order Selection Residual Tests
Prof. S. Mukhopadhyay

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Lec-28 Practical Issues in Identification
Prof. S. Mukhopadhyay

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Lec-29 Estimation Problems in Instrumentation and Control
Prof. S. Mukhopadhyay

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Lec-30 Conclusion
Prof. S. Mukhopadhyay

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