This project implements a Radial Basis Function Neural Network with Gaussian kernel function and constant spread function. The implementation uses all points in the input as centers for the Radial ...
This project implements a 2-layer RBF network that learns to approximate the target function f(p) = sin(p) for p ∈ [0, π]. The network uses Gaussian activation functions in the hidden layer and linear ...
Abstract: This paper proposes a novel continuous radial basis function neural network adaptive finite-time sliding mode control approach based on a barrier function for multiple virtual inertia ...
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