We establish the functional equivalence of a generalized class of Gaussian radial basis function (RBFs) networks and the full Takagi-Sugeno model (1983) of fuzzy inference. This generalizes an existing result which applies to the standard Gaussian RBF network and a restricted form of the Takagi-Sugeno fuzzy system. The more general framework allows the removal of some of the restrictive conditions of the previous result
This paper examines the underlying relationship between radial basis function artificial neural netw...
In this paper we discuss the learning problem of Radial Basis Function (RBF) Neural Networks. We pro...
In this paper we discuss the learning problem of Radial Basis Function (RBF) Neural Networks. We pro...
We establish the functional equivalence of a generalized class of Gaussian radial basis function (RB...
[[abstract]]It is shown that, under some minor restrictions, the functional behavior of radial basis...
The above paper claims that under a set of minor restrictions radial basis function networks and fuz...
The above paper claims that under a set of minor restrictions radial basis function networks and fuz...
The above paper claims that under a set of minor restrictions radial basis function networks and fuz...
Radial basis function networks and fuzzy rule systems are functionally equivalent under some mild co...
We address the dimensionality problem in the training of basis function networks of various types. S...
This paper proposes a new General Type-2 Radial Basis Function Neural Network (GT2-RBFNN) that is fu...
This paper examines the underlying relationship between radial basis function artificial neural netw...
Abstract—Radial basis function (RBF) networks have advan-tages of easy design, good generalization, ...
The conditions under which spline-based networks are functionally equivalent to the Takagi-Sugeno mo...
This paper examines the underlying relationship between radial basis function artificial neural netw...
This paper examines the underlying relationship between radial basis function artificial neural netw...
In this paper we discuss the learning problem of Radial Basis Function (RBF) Neural Networks. We pro...
In this paper we discuss the learning problem of Radial Basis Function (RBF) Neural Networks. We pro...
We establish the functional equivalence of a generalized class of Gaussian radial basis function (RB...
[[abstract]]It is shown that, under some minor restrictions, the functional behavior of radial basis...
The above paper claims that under a set of minor restrictions radial basis function networks and fuz...
The above paper claims that under a set of minor restrictions radial basis function networks and fuz...
The above paper claims that under a set of minor restrictions radial basis function networks and fuz...
Radial basis function networks and fuzzy rule systems are functionally equivalent under some mild co...
We address the dimensionality problem in the training of basis function networks of various types. S...
This paper proposes a new General Type-2 Radial Basis Function Neural Network (GT2-RBFNN) that is fu...
This paper examines the underlying relationship between radial basis function artificial neural netw...
Abstract—Radial basis function (RBF) networks have advan-tages of easy design, good generalization, ...
The conditions under which spline-based networks are functionally equivalent to the Takagi-Sugeno mo...
This paper examines the underlying relationship between radial basis function artificial neural netw...
This paper examines the underlying relationship between radial basis function artificial neural netw...
In this paper we discuss the learning problem of Radial Basis Function (RBF) Neural Networks. We pro...
In this paper we discuss the learning problem of Radial Basis Function (RBF) Neural Networks. We pro...