In this paper a three-layered perceptron is derived that exactly solves the problem of sorting n numbers. The perceptron configuration has O(n^2) nodes and can be viewed as a neural implementation of the parallel enumerative sorting algorithm developed by Preparata. Furthermore, it is shown that the problem of sorting n numbers cannot be solved exactly by a two-layered perceptron. Keywords: Sorting, Combinatorial Optimization, Neural Network, Multi-Layered Perceptron, Classification
[[abstract]]In this paper, we present an O(1) time neural network with O(n1 + var epsilon) neurons a...
[[abstract]]In this report, we prove that we can't construct a three-stage sorting network for sorti...
Abstract. Sorting Networks (SN) are efficient tools to sort an input data sequence. They are compose...
We consider the construction of minimal multi-layered perceptrons for solving combinatorial optimiza...
We consider the construction of minimal multilayered perceptrons for solving combinatorial optimizat...
We consider the construction of minimal multilayered perceptrons for solving combinatorial optimizat...
[[abstract]]A multilayer feedforward neural network is proposed to solve sorting problems. The netwo...
In this paper we consider the problem of determining the minimal number of layers required by a mult...
This paper proposes two simulations of sorting networks with spiking neural P systems. A comparison...
[[abstract]]Neural network is a proper model for parallel computing because it can process the data ...
We investigate the network complexity of multi-layered perceptrons for solving ex-actly a given prob...
We investigate the network complexity of multilayered perceptrons for solving exactly a given proble...
: combinatorial optimization is an active field of research in Neural Networks. Since the first atte...
The problem of relevance ranking consists of sorting a set of objects with respect to a given criter...
A new realisation for n-input sorters is presented. Resorting to the neuron-MOS (νMOS) concept and t...
[[abstract]]In this paper, we present an O(1) time neural network with O(n1 + var epsilon) neurons a...
[[abstract]]In this report, we prove that we can't construct a three-stage sorting network for sorti...
Abstract. Sorting Networks (SN) are efficient tools to sort an input data sequence. They are compose...
We consider the construction of minimal multi-layered perceptrons for solving combinatorial optimiza...
We consider the construction of minimal multilayered perceptrons for solving combinatorial optimizat...
We consider the construction of minimal multilayered perceptrons for solving combinatorial optimizat...
[[abstract]]A multilayer feedforward neural network is proposed to solve sorting problems. The netwo...
In this paper we consider the problem of determining the minimal number of layers required by a mult...
This paper proposes two simulations of sorting networks with spiking neural P systems. A comparison...
[[abstract]]Neural network is a proper model for parallel computing because it can process the data ...
We investigate the network complexity of multi-layered perceptrons for solving ex-actly a given prob...
We investigate the network complexity of multilayered perceptrons for solving exactly a given proble...
: combinatorial optimization is an active field of research in Neural Networks. Since the first atte...
The problem of relevance ranking consists of sorting a set of objects with respect to a given criter...
A new realisation for n-input sorters is presented. Resorting to the neuron-MOS (νMOS) concept and t...
[[abstract]]In this paper, we present an O(1) time neural network with O(n1 + var epsilon) neurons a...
[[abstract]]In this report, we prove that we can't construct a three-stage sorting network for sorti...
Abstract. Sorting Networks (SN) are efficient tools to sort an input data sequence. They are compose...