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The learning network was programmed as a basis function neural network.
This led to adopt the default SPM canonical HR as a basis function in the GLM analysis, improving the statistical power of the analysis and bringing to more easily interpretable results.
Typically a Gaussian activation function producing a radial function of the distance between each hidden unit weight vector and each pattern vector is used as a basis function: (5) ρ (| | x i − c i | | ) = exp (− | | x i − c i | | σ 2 ) where σ indicates the neuron radius [ 40, 41].
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From this observation, the supposition made in this study is that a guidance law can be designed by representing the command as a product of a basis function vector and a constant coefficient vector.
Secondly, we assess the performance of a non-Gaussian spatial distance kernel by deploying kernels on graphs as the choice of a basis function, a procedure that is suitable for discrete input data structures.
In this approach, a feed-forward network such as a radial basis function (RBF) network is used to learn the forward kinematic map of the redundant manipulator.
In a recent paper, Siddiqui et al. introduced a kernel function to be used as a radial basis function (RBF) in image registration tasks.
Additionally, the inner product between two feature vectors is defined as a radial basis function (RBF) kernel to handle nonlinearity.
Firstly, the system is modeled as a Fuzzy Basis Function Network (FBFN) and its Relative Gain Array (RGA) is calculated based on the obtained fuzzy model.
In this case, the system designed to predict the presence of oil slicks wraps other artificial intelligence techniques such as a radial basis function networks, growing cell structures and principal components analysis in order to develop the different phases of the Case-based reasoning cycle.
To this end, we used a k-nearest neighbor classifier (K-NN) as well as a Support Vector Machine with a Radial Basis Function as kernel (SVM with RBF kernel).
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