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A simple analog circuit is presented which can play a neuron role in static-model-based neural networks implemented in the form of an integrated circuit. Operating in a transresistance mode it is suited to cooperate with transconductance synapses. As a result, its input signal is a current which is a sum of currents coming from the synapses. Summation of(More)
This paper presents a complementary metal-oxide-semiconductor (CMOS) implementation of a conscience mechanism used to improve the effectiveness of learning in the winner-takes-all (WTA) artificial neural networks (ANNs) realized at the transistor level. This mechanism makes it possible to eliminate the effect of the so-called ¿dead neurons,¿ which do not(More)
In this study, we present a hardware implementation of the conscience mechanism in Kohonen self-organizing maps. The proposed realization of the conscience mechanism is important to the functioning of the neural network as it eliminates so-called dead (inactive) neurons. As a result the network learning, the level quantization error can be reduced. The(More)
This paper presents an application of an artificial neural network to determine survival time of patients with a bladder cancer. Different learning methods have been investigated to find a solution, which is most optimal from a computational complexity point of view. In our study, a model of a multilayer perceptron with a training algorithm based on an(More)
In this paper, we present an experimental current-mode Kohonen neural network (KNN) implemented in a CMOS 0.18 Pm process. The network contains four output neurons. Each neuron has three analog weights related to three inputs. The presented KNN has been realized using building blocks proposed earlier by the authors, such as binary tree current-mode winner(More)
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