1. A radial basis function neural network system, which comprises: at least one signal input node adapted to receive environmental input data from an environmental data base; a non-linear activation layer comprising a plurality of activation functions, said activation layer having an input coupled to said signal input node and an output, each of said activation functions being selected from combinations of a global Mean Square Error (MSE) for all data points within said data base and a local MSE for a subset of data points within said data base, said activation functions being operable to modify said input data; a blocking layer comprising a plurality of selectively active blocking functions, said blocking layer having an input coupled to said output of said non-linear activation layer and an output, said blocking layer selectively operative to block selected modified input data and to selectively transmit other modified input data; a summer coupled to said output of said blocking layer, said summer operative to combine said transmitted modified environmental input data; and a signal output node coupled to said summer and operable to output said combined transmitted modified input data.