International Scholarly Research Notices / 2012 / Article / Fig 1

Review Article

Using Radial Basis Function Networks for Function Approximation and Classification

Figure 1

Architecture of the RBF network. The input, hidden, and output layers have 𝐽 1 , 𝐽 2 , and 𝐽 3 neurons, respectively. πœ™ 0 ( βƒ— π‘₯ ) = 1 corresponds to the bias in the output layer, while πœ™ 𝑖 ( βƒ— π‘₯ ) ’s denote the nonlinearity at the hidden nodes.

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