Current Slide

Small screen detected. You are viewing the mobile version of SlideWiki. If you wish to edit slides you will need to use a larger device.

Algorithm for ANN Learning

  • Learning is based on training data, and aims at appropriate weights for the perceptrons in a network.

  • Direct computation is in the general case not feasible.

  • An initial random assignment of weights simplifies the learning process that becomes an iterative adjustment process.

  • In the case of single perceptrons, learning becomes the process of moving hyperplanes around; parametrized over time t: Wi(t+1) = Wi(t) + Δ Wi(t)


Speaker notes:

Content Tools

Sources

There are currently no sources for this slide.