Transcription of 7 The Backpropagation Algorithm - fu-berlin.de
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7 The Backpropagation Algorithm - fu-berlin.de
R. Rojas: Neural Networks, Springer-Verlag, Berlin, 19967 The Backpropagation Learning as gradient descentWe saw in the last chapter that multilayered networks are capable of com-puting a wider range of Boolean functions than networks witha single layerof computing units. However the computational effort neededfor finding thecorrect combination of weights increases substantially when more parametersand more complicated topologies are considered. In this chapter we discuss apopular learning method capable of handling such large learning problems the Backpropagation Algorithm . This numerical method was used by differentresearch communities in different contexts, was discoveredand rediscovered,until in 1985 it found its way into connectionist AI mainly through the work ofthe PDP group [382].
function sc: IR →(0,1) defined by the expression sc(x) = 1 1+e−cx. The constant ccan be selected arbitrarily and its reciprocal 1/cis called the temperature parameter in stochastic neural networks. The shape of the sigmoid changes according to the value of c, as can be seen in Figure 7.1. The graph shows the shape of the sigmoid for c= 1 ...
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