Add to ORKGwww.elsevier.com/locate/neucom N-bit parity neural networks:new solutions based on linear programmin
A fast parsimonious linear-programming-based algorithm for training neural networks is proposed that...
AbstractThe even-odd parity problem is a tough one for neural networks to handle because they assume...
This paper is concerned with neural networks which have the ability to solve linear and nonlinear co...
Abstract:- Highly nonlinear data sets are important in the field of artificial neural networks. It i...
Starting with two hidden units, we train a simple single hidden layer feed-forward neural network to...
In this paper ordered neural networks for the Nbit parity function containing [log2(N + 1)] threshol...
An algorithm for the training of a special multilayered feed-forward neural network is presented. Th...
Abstract. A universal binary neuron (UBN) operates with the complex-valued weights and the complex-v...
A universal binary neuron (UBN) operates with complex-valued weights and a complex-valued activation...
A neural network is proposed for solving linear and quadratic programming problems. The main feature...
An algorithm for the training of multilayered feedforward neural networks is presented. The strategy...
Interest in algorithms which dynamically construct neural networks has been growing in recent years....
This book aims to present a viable alternative to the Hopfield Neural Network (HNN) model for analog...
Abstract. This paper presents an approach to the joint optimization of neural network structure and ...
Neural cryptography is the application of artificial neural networks (ANNs) in the subject of crypto...
A fast parsimonious linear-programming-based algorithm for training neural networks is proposed that...
AbstractThe even-odd parity problem is a tough one for neural networks to handle because they assume...
This paper is concerned with neural networks which have the ability to solve linear and nonlinear co...
Abstract:- Highly nonlinear data sets are important in the field of artificial neural networks. It i...
Starting with two hidden units, we train a simple single hidden layer feed-forward neural network to...
In this paper ordered neural networks for the Nbit parity function containing [log2(N + 1)] threshol...
An algorithm for the training of a special multilayered feed-forward neural network is presented. Th...
Abstract. A universal binary neuron (UBN) operates with the complex-valued weights and the complex-v...
A universal binary neuron (UBN) operates with complex-valued weights and a complex-valued activation...
A neural network is proposed for solving linear and quadratic programming problems. The main feature...
An algorithm for the training of multilayered feedforward neural networks is presented. The strategy...
Interest in algorithms which dynamically construct neural networks has been growing in recent years....
This book aims to present a viable alternative to the Hopfield Neural Network (HNN) model for analog...
Abstract. This paper presents an approach to the joint optimization of neural network structure and ...
Neural cryptography is the application of artificial neural networks (ANNs) in the subject of crypto...
A fast parsimonious linear-programming-based algorithm for training neural networks is proposed that...
AbstractThe even-odd parity problem is a tough one for neural networks to handle because they assume...
This paper is concerned with neural networks which have the ability to solve linear and nonlinear co...