Estimation of Signals and Systems

Overview

Contents:
Introduction - Probability Theory -Random Variables - Function of Random Variable Joint Density - Mean and Variance - Random Vectors Random Processes - Random Processes and Linear Systems - Some Numerical Problems -Miscellaneous Topics on Random Process - Linear Signal Models - Linear Mean Square Error Estimation - Auto Correlation and Power Spectrum Estimation - Z-Transform Revisited Eigen Vectors/Values

The Concept of Innovation - Last Squares Estimation Optimal IIR Filters - Introduction to Adaptive FIlters-State Estimation - Kalman Filter - Model and Derivation I - Estimator Properties-The Time-Invariant Kalman Filter - Kalman Filte r- Case Study - System identification Introductory Concepts - Linear Regression - Recursive Least Squares - Variants of LSE-Least Square Estimation - Model Order Selection Residual Tests - Practical Issues in Identification - Estimation Problems in Instrumentation and Control