ISRC

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
The contrast enhanced image is sent to an
automatic feature detection stage
Magnetic resonance brain scan. After some
preprocessing
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
  (ECE171AB)
• 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
• Introduction to Intelligent Systems and
  Sensor-based Robots
• Model-Based approach in perception
• Image segmentation
• Edge Detection
• Region growing
• Texture analysis
• Object recognition and image understanding
• Extraction of 3-dimensional cues passive and
  active approaches
• Project (about 5 weeks long)
• Vehicle Detection Re-identification
• Person Detection and Tracking
• Robust Image Classification

Image Classified as a Day Image
Input 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 machinelearning.

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ECE 174 Intro to Linear Nonlinear Optimization
Benefits

• 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

11
ECE 171AB Classical and State-Space Control
Systems
Benefits

• 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

12
ECE 173 Neural Networks (NNs) and Fuzzy Logic
(FL)
Benefits

• Theory of Neural Networks and training of NNs
• Feedforward vs. recurrent NNs
• NNs for Pattern Classification and Functional
  Approximation
• NNs 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
• Manufacturingand more

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