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Self-organizing maps architecture

Not all neural networks are the same their connections, elemental functions, training methods and applications may differ in significant ways. The types of elements in a network and the connections between them are referred to as the network architecture. Commonly used elements in artificial neural networks will be presented in Chapter 2. The multilayer perception, one of the most commonly used architectures, is described in Chapter 3. Other architectures, such as radial basis function networks and self organizing maps (SOM) or Kohonen architectures, will be described in Chapter 4. [Pg.17]


See other pages where Self-organizing maps architecture is mentioned: [Pg.323]    [Pg.18]    [Pg.51]    [Pg.62]    [Pg.93]    [Pg.258]    [Pg.540]    [Pg.71]    [Pg.663]    [Pg.87]    [Pg.142]    [Pg.157]    [Pg.57]   
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