In neural networks, there are a number of architectures implementing unsupervised learning; however, the scope of this book will cover only two: a neural network of radial basis functions and a Kohonen neural network.
This neural network architecture has three layers and combines two types of learning, as shown in the following figure:
For the hidden layer, competitive learning is applied in order to activate one of the radial basis functions in the hidden neurons. The radial basis function takes the form of Gaussian functions:
where d is the distance vector between the input x