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An analog implementation of radial basis neural networks (RBNN) using BiCMOS technology
(2001-12-01)
This paper describes a analog implementation of radial basis neural networks (RBNN) in BiCMOS technology. The RBNN uses a gaussian function obtained through the characteristic of the bipolar differential pair. The gaussian ...
An analog implementation of radial basis neural networks (RBNN) using BiCMOS technology
(2001-12-01)
This paper describes a analog implementation of radial basis neural networks (RBNN) in BiCMOS technology. The RBNN uses a gaussian function obtained through the characteristic of the bipolar differential pair. The gaussian ...
Radial basis function networks with quantized parameters
(2008-09-30)
A RBFN implemented with quantized parameters is proposed and the relative or limited approximation property is presented. Simulation results for sinusoidal function approximation with various quantization levels are shown. ...
Radial basis function networks with quantized parameters
(2008-09-30)
A RBFN implemented with quantized parameters is proposed and the relative or limited approximation property is presented. Simulation results for sinusoidal function approximation with various quantization levels are shown. ...
RBF circuits based on folded cascode differential pairs
(2008-12-01)
We propose new circuits for the implementation of Radial Basis Functions such as Gaussian and Gaussian-like functions. These RBFs are obtained by the subtraction of two differential pair output currents in a folded cascode ...
RBF circuits based on folded cascode differential pairs
(2008-12-01)
We propose new circuits for the implementation of Radial Basis Functions such as Gaussian and Gaussian-like functions. These RBFs are obtained by the subtraction of two differential pair output currents in a folded cascode ...