quiz3_2008

Z 1 1 e z so for the output layer of a sigmoid neural

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: z ∂wi Substituting (3) and (4) into (2): (5) ∂P ∂P ∂y i = = ( y * − y ) y (1 − y ) xi ∂wi ∂yi ∂wi Substituting (5) into the weight equation (1): wi' = wi + r( y * − y ) y (1 − y ) xi ... which can be written in terms of δ, which is the derivative of P with respect to total input, ∂P ∂y = ( y * − y ) y (1 − y ) = y (1 − y )( y * − y ) wi ∂y ∂z xi ∂P into this equation.) (Note that to change P, one only needs to substitute the new ∂y wi' = wi + rδixi , where δi = ∂P : ∂z δi yi For an inner node, we use a similar equation that takes into account the output yi for that node, and the δ and w values for the next layer, where "next layer" means the neighboring nodes one layer closer to the output layer: wij wi δi y = x δj y y h = xi j i j wi' = wi + rδixi , where δi = yi(1 − yi) δjwij ∑ and wij is the weight between layers i and j. ... Summary: For each layer, wi' = wi + rδixi , where for outer layer δi = y (1 − y )( y * − y ) ∑δ w inner layer δi = yi(1 − yi) j ij 11...
View Full Document

This document was uploaded on 03/17/2014 for the course EECS 6.034 at MIT.

Ask a homework question - tutors are online