AI

1. ISRC & Controls
Undergraduate Depth Sequence Workshop
March 1, 2006

2. Intelligent Systems…
 Sense the World
 DSP, Image Processing, Statistical Data Collection
 Extract Information About the World
 Feature Extraction, Neural Network and Fuzzy Learning, Data Compression
 Recognize the State of the World
 Statistical & Neural Network Pattern Recognition, Detection Theory
 Predict the Behavior of the World
 Probability, Time Series Analysis, Dynamical Systems Theory
 Reason About the World and Plan Actions
 Artificial Intelligence, Decision Theory
 Act on, and Communicate with, the World
 Control Theory, Robotics, Information & Communications Theory

3. Example: Automated Medical
Diagnosis
Magnetic resonance brain
scan. After some
preprocessing…
The contrast enhanced image is
sent to an automatic feature
detection stage…

4. Example: Automated Medical
Diagnosis - continued
 Informative Features are Extracted and Patterns are
Recognized:
 A Bayesian Diagnostic
Reasoning Engine is Invoked:

5. Machine Intelligence and
Controls Applications
 Weather and Natural
Disaster Prediction
 Speech and Image
Recognition
 Biomedical imaging
and Diagnosis
 Manufacturing and
Robotics
 Automotive Systems
 Stock Market and
Economic Prediction
 Aerospace Systems
 Electromagnetic Device
Control & Optimization
 Computer games and
Virtual reality
 Genomics and
Bioinformatics
 Agricultural and
Industrial inspection
 Industrial Optimization
Just to name a few…

6. ISRC Depth Requirement
 Introduction to Intelligent Systems: Robotics
and Machine Intelligence (ECE172A)
 Neural Networks & Fuzzy Logic (ECE173)
 Introduction to Linear and Nonlinear
Optimization with Applications (ECE174)
 Elements of Machine Learning (ECE175)
 Introduction to DSP (ECE161A)
or ECE161A, 187, 253A, 285, Cogsci108F
(Medical Imaging, Advanced Neural Networks, … )

7. Controls Depth Requirement
 Classical & State-Space Linear Control
Systems (ECE171A&B)
 Introduction to Linear and Nonlinear
Optimization with Applications
(ECE174)
 Neural Networks & Fuzzy Logic
(ECE173)
 Computer Interfacing (ECE118)

8. ECE 172A – Introduction to
Intelligent Systems
Main topics covered in the course
include:
1. Introduction to Intelligent Systems and
Sensor-based Robots
2. Model-Based approach in perception
3. Image segmentation
4. Edge Detection
5. Region growing
6. Texture analysis
7. Object recognition and image
understanding
8. Extraction of 3-dimensional cues:
passive and active approaches
Project (about 5 weeks long):
1. Vehicle Detection & Re-identification
2. Person Detection and Tracking
3. Robust Image Classification
Input Image
Image Classified as a
Day Image

9. 175: Elements of machine
intelligence
 introduction to machine learning.
 decision functions.
 statistical pattern classifiers.
 generative vs. discriminant
methods
 feature selection.
 regression.
 clustering.
 applications of machine
learning.

10. ECE 174 – Intro to Linear &
Nonlinear Optimization
 Linear & Nonlinear Inverse
Problems
 Regularization of Ill-Posed
Problems
 Projection Theorem and the
Geometry of Linear
Operators
 Least-Squares and the
Pseudoinverse
 Application Computer
Projects
 Many practical, real-world
algorithms are based on
least-squares solutions
 Project Reports Make
Impressive Additions to Job
Interview Portfolios
 Students from 174 have
been hired by companies
which do
 Signal processing
 Speech compression
 GPS navigation
Benefits:

11. ECE 171AB – Classical and
State-Space Control Systems
 Theory of SISO LTI Systems in
the Time & Frequency
Domains
 Transient and Steady State
Behavior
 Continuous vs Discrete-Time
Control Systems
 Frequency Domain
Stabilization Techniques
 Design of Controllers and
Compensators
 State-Space Modeling of
Complex Multivariable
Systems
 Used to provide high-
performance control of
electromechanical systems
 Many important real-world
applications and jobs:
 Disk Drive Industry
 Printer Industry
 Automotive Industry
 Aerospace Industry
 Manufacturing
Benefits:

12. ECE 173 – Neural Networks
(NN’s) and Fuzzy Logic (FL)
 Theory of Neural Networks and
training of NN’s
 Feedforward vs. recurrent
NN’s
 NN’s for Pattern Classification
and Functional Approximation
 NN’s for Adaptive Control
 Theory of Fuzzy Logic and
Reasoning
 Theory of Fuzzy Control
 Computer Projects
 Applications to Decision,
Modeling, and Control of
Highly Uncertain and
Nonlinear Systems
 Many important real-world
applications and jobs:
 Disk Drive Industry
 Printer Industry
 Automotive Industry
 Aerospace Industry
 Manufacturing
and more…
Benefits:

13. ECE 161A: Introduction to DSP
 Discrete-time signals and systems
 Frequency-domain characterization
 Analysis of discrete-time systems
 Z-transform
 Linear-phase, Minimum-phase and Allpass
systems

14. ECE 118: Computer Interfacing
 Interfacing computers and embedded
controllers to devices & the real world
 Busses, interrupts, DMA, memory
mapping, concurrency
 Serial/parallel communications, real-time
I/O, closed loop control.
 Design & construct an interfacing project