This course covers lessons on probability theory,random variables,mean and variance,linear signal models,Z-transform,kalman filter,variants of LSE and estimation problems in instrumentation and control....
This course covers lessons on probability theory,random variables,mean and variance,linear signal models,Z-transform,kalman filter,variants of LSE and estimation problems in instrumentation and control....
Introduction
43mProbability Theory
46mRandom Variables
53mFunction of Random Variable Joint Density
55mMean and Variance
54mRandom Vectors Random Processes
48mRandom Processes and Linear Systems
46mSome Numerical Problems
54mMiscellaneous Topics on Random Process
51mLinear Signal Models
58mLinear Mean Sq.Error Estimation
54mAuto Correlation and Power Spectrum Estimation
45mZ-Transform Revisited Eigen Vectors/Values
52mThe Concept of Innovation
53mLast Squares Estimation Optimal IIR Filters
50mIntroduction to Adaptive Filters
47mState Estimation
53mKalman Filter-Model and Derivation
50mKalman Filter-Derivation (Contd...)
50mEstimator Properties
49mThe Time-Invariant Kalman Filter
52mKalman Filter-Case Study
53mSystem identification Introductory Concepts
54mLinear Regression-Recursive Least Squares
49mVariants of LSE
49mLeast Square Estimation
51mModel Order Selection Residual Tests
53mPractical Issues in Identification
55mEstimation Problems in Instrumentation and Control
55mConclusion
55m