Multi Sensor Data Fusion – Using Fuzzy Logic and Neural Networks D1408

Learning outcome

A candidate who has passed the course will have a learning outcome in the form of acquired knowledge, skills, and general competence, as described below.

Knowledge

The candidate:

  • will understand inferential methods based on, fuzzy, neural and fuzzy-neural methods
  • can explain the basics of neural networks
  • can explain what fuzzification and defuzzification are
  • can identify strategies for using multi sensor data fusion, fuzzy logic, neural networks for soft sensor applications
  • can describe fuzzy-neural approach in solving a problem

Skills

The candidate will be able to:

  • apply theory of fuzzy logic, neural networks and fuzzy-neural methods to data fusion and soft sensors
  • appraise the key issues related to fuzzy logic for a concrete application
  • compare different inferential methods based solutions for various case studies
  • design soft sensor using inferential methods

General competence

The candidate will be able to:

  • communicate acquired knowledge in specific subtopics involving concrete practical assignments in the form of technical reports and oral presentations to peers and staff
  • publish some of the outcomes from assignments

Course Description

  • Multi Sensor Data Fusion (MSDF)
  • Architectures for the interaction of fusion nodes
  • Neural Netwok architecture
  • Fuzzy Logic
  • Neural Network
  • Fuzzy-neural methods
  • Sensor networking
  • Support vector machines
  • Markov Chains

Teaching and Learning Methods

Teaching will be based on lectures, assignments and data analysis using dedicated programs. During the semester the students will work with several assignments. These assignments will be based on problem based learning providing better understanding of specific subtopics in the course.

Assessment Methods

A set of mandatory assignments count 40% and an individual written final test counts 60% of the final grade. No study aids are permitted during the final written exam. The assignments and the final test are used to assess knowledge and skills. The assignments are also used to assess general competence.

Minor adjustments may occur during the academic year, subject to the decision of the Dean

Publisert av / forfatter Unni Stamland Kaasin <Unni.S.KaasinSPAMFILTER@hit.no> - 21/12/2015