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- Enrique Mérida Casermeiro, Gloria Galán Marín, José Muñoz-Pérez
- Neural Processing Letters
- 2001

In this Letter we show that discrete multivalued Hopfield-type neural networks enable a relatively easy formulation of the Traveling Salesman Problem compared to the traditional Hopfield model. Thus, with the multivalued representation the network can be easily confined to feasible solutions, avoiding the need to tune any parameter. An investigation into… (More)

- Gloria Galán Marín, Enrique Mérida Casermeiro, Domingo López-Rodríguez
- Neural Processing Letters
- 2007

Detection of isomorphism among kinematic chains is essential in mechanical design, but difficult and computationally expensive. It has been shown that both traditional methods and previously presented neural networks still have a lot to be desired in aspects such as simplifying procedure of identification and adapting automatic computation. Therefore, a new… (More)

- Jesús Medina, Enrique Mérida Casermeiro, Manuel Ojeda-Aciego
- J. Applied Logic
- 2004

We present a neural net based implementation of propositional [0, 1]-valued multiadjoint logic programming. The implementation needs some preprocessing of the initial program to transform it in a homogeneous program; then, transformation rules carry programs into neural networks, where truth-values of rules relate to output of neurons, truth-values of facts… (More)

- Gloria Galán Marín, Enrique Mérida Casermeiro, José Muñoz-Pérez
- Computers & OR
- 2003

- Jesús Medina, Enrique Mérida Casermeiro, Manuel Ojeda-Aciego
- IBERAMIA
- 2004

The theory of multi-adjoint logic programs has been introduced as a unifying framework to deal with uncertainty, imprecise data or incomplete information. From the applicative part, a neural net based implementation of homogeneous propositional multi-adjoint logic programming on the unit interval has been presented elsewhere, but restricted to the case in… (More)

A neural net based development of multi-adjoint logic programming is presented. Transformation rules carry programs into neural networks, where truth-values of rules relate to output of neurons, truth-values of facts represent input, and network functions are determined by a set of general operators; the output of the net being the values of propositional… (More)

- Gabriel Aguilera Venegas, José Luis Galán García, Enrique Mérida Casermeiro, Pedro Rodríguez Cielos
- Mathematics and Computers in Simulation
- 2014

- Enrique Mérida Casermeiro, José Muñoz-Pérez
- Journal of Intelligent and Fuzzy Systems
- 2002

A neural approach to propositional multi-adjoint logic programming was recently introduced. In this paper we extend the neural approach to multi-adjoint deduction and, furthermore, modify it to cope with abductive multi-adjoint reasoning, where adaptations of the uncertainty factor in a knowledge base are carried out automatically so that a number of given… (More)