Radial Basis Functions Neuron Model Network Architecture Exact Design (newrbe)

1. Radial Basis Functions • Neuron Model • Network Architecture • Exact Design (newrbe) • More Efficient Design (newrb) • Generalized Regression Networks (GRNN) • Probabilistic Neural Networks

2. RadialBasis Networks Neuron Model

3. The radial basis function has a maximum of 1 when its input is 0. As the distance between w and p decreases, the output increases. Thus, a radial basis neuron acts as a detector that produces 1 whenever the input p is identical to its weight vector p.

4. Network Architecture: Where R = number of elements in input vector. S1= number of neurons layer 1 S2= number of neurons in layer 2

5. Generalized Regression Networks • Generalized regression networks (GRNN) is often used for function approximation. Network architecture

6. Probabilistic Neural Networks • Probabilistic neural networks can be used for classification problems. Network architecture

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