ECE 992 (01) - Advanced Topics in Electrical Engineering

Adv Topics Electrical Engineer

Durham   Engineering&Physical Sciences :: Electrical&Comp Engineering
Credits: 3.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 10737
Example of a recent topic: analog VLSI design. May be repeated.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Instructors: Diliang Chen

Times & Locations

Start Date End Date Days Time Location
8/29/2022 12/12/2022 TR 11:10am - 12:30pm KING N204
Additional Course Details: 

[Topics for Fall 2022

Multi-Sensor Data Fusion for Internet of Things Applications


Diliang Chen, Ph.D.

Office: Kingsbury W207


Office hour: Scheduled on request. Please send me an email to schedule office hour.

Course Description:

Multi-sensor data fusion is a technique of combining and integrating of data from multiple sensors to provide a more accurate and reliable view of data. This course aims to provide both insight understanding of theories and hands-on experiences related to multi-sensor data fusion. Lectures will provide a comprehensive introduction to effective sensor and data fusion methods that improve the probability of object tracking, target detection, classification, and identification. Hands-on projects will enhance the understanding and the application of each data fusion methods.

Credits: 3

Topics Covered:

  • Introduction on estimation theories and sensor fusion
  • Sensor and data fusion architectures
  • Kalman Filter (Linear, Extended, Unscented)
  • Bayesian Networks
  • Particle filter
  • Convolutional Neural Networks

Learning Outcomes:

After taking this course, you will be able to:

  • Understand the advantages of multi-sensor data fusion for object tracking and state estimation
  • Understand the architectures for sensor fusion
  • Be familiar with the processes of Multi-sensor data fusion
  • Identify suitable multi-sensor data fusion algorithms for practical applications
  • Implement different multi-sensor data fusion algorithms with MATLAB