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Course Description

A signal as referred to in communication systems, signal processing, and electrical engineering "is a function that conveys information about the behavior or attributes of some phenomenon"

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Course Syllabus
  • Lec-1 Introduction
  • Lec-2 Probability Theory
  • Lec-3 Random Variables
  • Lec-4 Function of Random Variable Joint Density
  • Lec-5 Mean and Variance
  • Lec-6 Random Vectors Random Processes
  • Lec-7 Random Processes and Linear Systems
  • Lec-8 Some Numerical Problems
  • Lec-9 Miscellaneous Topics on Random Process
  • Lec-10 Linear Signal Models
  • Lec-11 Linear Mean Sq.Error Estimation
  • Lec-12 Auto Correlation and Power Spectrum Estimation
  • lec-13 Z-Transform Revisited Eigen Vectors/Values
  • Lec-14 The Concept of Innovation
  • Lec-15 Last Squares Estimation Optimal IIR Filters
  • Lec-16 Introduction to Adaptive FIlters
  • Lec-17 State Estimation
  • Lec-18 Kalman Filter-Model and Derivation
  • Lec-19 Kalman Filter-Derivation(Contd...)
  • Lec-20 Estimator Properties
  • Lec-21 The Time-Invariant Kalman Filter
  • Lec-22 Kalman Filter-Case Study
  • Lec-24 Linear Regression-Recursive Least Squares
  • Lec-25 Variants of LSE
  • Lec-26 Least Square Estimation
  • Lec-27 Model Order Selection Residual Tests
  • Lec-28 Practical Issues in Identification
  • Lec-29 Estimation Problems in Instrumentation and Control
  • Lec-30 Conclusion
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