Chapter 6 Architecture and Equilibria 6.1 Neutral Network As Stochastic Gradient system Classify Neutral network model By their synaptic connection topolgies and by how learning modifies their connection topologies synaptic connection topolgies 1.feedforward.if No closed synaptic loops 2.feedback if closed synapticloops orfeedback pathways how learning modifies their connection topologies 1.Supervised learning use class-membership inf ormation of training samplings 2.Unsup ervised learning use unlabelled training samplings 2004.11.10 32004.11.10 3 Chapter 6 Architecture and Equilibria 6.1 Neutral Network As Stochastic Gradient system Classify Neutral network model By their synaptic connection topolgies and by how learning modifies their connection topologies    feedback i f closed synapticloops orfeedback pathways feedforward i f No closed synaptic loops 2. . 1. .      − Un ervised learning use unlabelled training samplings training samplings Supervised learning use class membership ormation of 2. sup : 1. : inf synaptic connection topolgies how learning modifies their connection topologies