We have fabricated a PCA (Principal Component Analysis) learning network in a FPGA (Field Programmable Gate Array) by using an asynchronous PDM (Pulse Density Modulation) digital ...
Input selection in the nonlinear function approximation is important and difficult problem. Neural networks provide good generalization in many cases, but their interpretability is...
The dynamics of neural and other automata networks are defined to a large extent by their topologies. Artificial evolution constitutes a practical means by which an optimal topolog...
In our recent work, a general method called the stable state analysis technique was developed to determine constraints that the weights in the Hopfield energy function must satisf...
The solving of least square systems is a useful operation in neurocomputational modeling of learning, pattern matching, and pattern recognition. In these last two cases, the soluti...