Lecture Notes | Signals, Systems and Inference | Electrical Engineering and Computer Science | MIT OpenCourseWare

Lecture Notes

6.011 Signals, Systems and Inference, Lecture 1 Introduction

6.011 Signals, Systems and Inference, Lecture 10 Observers, State Feedback

6.011 Signals, Systems and Inference, Lecture 11 State Feedback, Observer-Based Feedback

6.011 Signals, Systems and Inference, Lecture 12 Probabilistic Models, Random Variables

6.011 Signals, Systems and Inference, Lecture 13 Vector Picture for First- and Second-Order Statistics, MMSE and LMMSE Estimation

6.011 Signals, Systems and Inference, Lecture 14 LMMSE Estimation, Orthogonality

6.011 Signals, Systems and Inference, Lecture 15 Normal Equations, Random Processes

6.011 Signals, Systems and Inference, Lecture 16 Wide-sense Stationary Processes, LTI Filtering of WSS Processes

6.011 Signals, Systems and Inference, Lecture 17 LTI Filtering of WSS Processes

6.011 Signals, Systems and Inference, Lecture 18 Power Spectral Density

6.011 Signals, Systems and Inference, Lecture 19 Einstein-Wiener-Khinchin Theorem, PSD Applications, Modeling Filters

6.011 Signals, Systems and Inference, Lecture 2 Transforms

6.011 Signals, Systems and Inference, Lecture 20 Wiener Filtering

6.011 Signals, Systems and Inference, Lecture 21 Wiener Filtering Illustrations

6.011 Signals, Systems and Inference, Lecture 22 Hypothesis Testing

6.011 Signals, Systems and Inference, Lecture 23 Neyman-Pearson Testing, Signal Detection

6.011 Signals, Systems and Inference, Lecture 24 Matched Filtering

6.011 Signals, Systems and Inference, Lecture 3 Energy Spectral Density

6.011 Signals, Systems and Inference, Lecture 4 State-Space Models

6.011 Signals, Systems and Inference, Lecture 5 State-Space Models, Equilibrium, Linearization

6.011 Signals, Systems and Inference, Lecture 6 Modal Solution of Undriven CT LTI State-Space Models

6.011 Signals, Systems and Inference, Lecture 7 Full Modal Solution, Asymptotic Stability, Reachability and Observability

6.011 Signals, Systems and Inference, Lecture 8 Matrix Exponential, ZIR+ZSR, Transfer Function, Hidden Modes, Reaching Target States

6.011 Signals, Systems and Inference, Lecture 9 Observers for State Estimation

Course Info

Instructors

Departments

Electrical Engineering and Computer Science

As Taught In

Spring 2018

Level

Undergraduate

Topics

Engineering
- Electrical Engineering

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