/Artificial-Neural-Networks

course lab of DD2432 artificial neural network and other learning system at KTH

Primary LanguageMercury

Artificial-Neural-Networks

Course lab of DD2432 Artifical Neural Network and Other Learning Systems at KTH.

Contents

lab 1: feedforward networks [slide]

  • one-layer-perceptron network
  • two-layer-perceptron network

lab 2: RBF networks [slide]

  • supervised learning of weights (batch learning with least square; online learning with delta rule)
  • RBF placement (competitive learning; expectation maximization)

lab 3: self-organizing maps [slide]

  • data clustering

lab 4: Hopfield networks [slide]

  • Hebbian learning
  • synchronous and asynchronous pattern update