6.011 | Spring 2018 | Undergraduate
Signals, Systems and Inference

Lecture Slides

Ses # Topic Lecture Slides
1 Introduction Lecture 1 Slides (PDF - 1.1MB)
2 Transforms Lecture 2 Slides (PDF)
3 Energy Spectral Density Lecture 3 Slides (PDF)
4 State-Space Models Lecture 4 Slides (PDF)
5

State-Space Models

Equilibrium

Linearization

Lecture 5 Slides (PDF)
6

Modal Solution of Undriven CT

LTI State-Space Models

Lecture 6 Slides (PDF)
7

Full Modal Solution

Asymptotic Stability

Reachability

Observability

Lecture 7 Slides (PDF)
8

Matrix Exponential

ZIR+ZSR

Transfer Function

Hidden Modes

Reaching Target States

Lecture 8 Slides (PDF)
9 Observers for State Estimation Lecture 9 Slides (PDF)
10

Observers

State Feedback

Lecture 10 Slides (PDF)
11

State Feedback

Observer-Based Feedback

Lecture 11 Slides (PDF)
12

Probabilistic Models

Random Variables

Lecture 12 Slides (PDF)
13

Vector Picture for First- and Second-Order Statistics

MMSE and LMMSE Estimation

Lecture 13 Slides (PDF)
14

LMMSE Estimation

Orthogonality

Lecture 14 Slides (PDF)
15

Normal Equations

Random Processes

Lecture 15 Slides (PDF)
16

Wide-Sense Stationary Processes

LTI Filtering of WSS Processes

Lecture 16 Slides (PDF)
17 LTI Filtering of WSS Processes Lecture 17 Slides (PDF)
18 Power Spectral Density (PSD) Lecture 18 Slides (PDF)
19

Einstein-Wiener-Khinchin Theorem

PSD Applications

Modeling Filters

Lecture 19 Slides (PDF)
20 Wiener Filtering Lecture 20 Slides (PDF)
21 Wiener Filtering Illustrations Lecture 21 Slides (PDF)
22 Hypothesis Testing Lecture 22 Slides (PDF)
23

Neyman-Pearson Testing

Signal Detection

Lecture 23 Slides (PDF)
24 Matched Filtering Lecture 24 Slides (PDF)
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