1994, Vol. I, Núm. 2
http://hdl.handle.net/2099/1492
2024-10-11T03:25:00ZInformation systems in categories of valued relations
http://hdl.handle.net/2099/2447
Information systems in categories of valued relations
Gisin, Vladimir B.
The paper presents a categorical version of the notion of information system due to D. Scott. The notion of information system is determined in the framework of ordered categories with involution and division and the category of information systems is constructed. The essential role in all definitions and constructions play correlations between inclusion relations and entailment relations.
2007-03-05T17:04:20ZGisin, Vladimir B.The paper presents a categorical version of the notion of information system due to D. Scott. The notion of information system is determined in the framework of ordered categories with involution and division and the category of information systems is constructed. The essential role in all definitions and constructions play correlations between inclusion relations and entailment relations.Operating on formal concept abstraction
http://hdl.handle.net/2099/2446
Operating on formal concept abstraction
Arigoni, Anio O.; Rossi, Andrea
The subject of this paper regards a procedure to obtain the abstract from of concepts, directly from their most natural form, thus these can be efficiently learned and the possibility of operating formally on them is reached. The achievement of said type of form results also useful to compute conceptual parameters symbolic and numerical in nature.
2007-03-05T17:00:12ZArigoni, Anio O.Rossi, AndreaThe subject of this paper regards a procedure to obtain the abstract from of concepts, directly from their most natural form, thus these can be efficiently learned and the possibility of operating formally on them is reached. The achievement of said type of form results also useful to compute conceptual parameters symbolic and numerical in nature.An effective way to generate neural network structures for function approximation
http://hdl.handle.net/2099/2445
An effective way to generate neural network structures for function approximation
Bastian, A.
One still open question in the area of research of multi-layer feedforward neural networks is concerning the number of neurons in its hidden layer(s). Especially in real life applications, this problem is often solved by heuristic methods. In this work an effective way to dynamically determine the number of hidden units in a three-layer feedforward neural network for function approximation is proposed.
2007-03-05T16:52:05ZBastian, A.One still open question in the area of research of multi-layer feedforward neural networks is concerning the number of neurons in its hidden layer(s). Especially in real life applications, this problem is often solved by heuristic methods. In this work an effective way to dynamically determine the number of hidden units in a three-layer feedforward neural network for function approximation is proposed.Between logic and probability
http://hdl.handle.net/2099/2439
Between logic and probability
Sales Porta, Ton
Logic and Probability, as theories, have been developed quite independently and, with a few exceptions (like Boole's), have largely ignored each other. And nevertheless they share a lot of similarities, as well a considerable common ground. The exploration of the shared concepts and their mathematical treatment and unification is here attempted following the lead of illustrious researchers (Reichenbach, Carnap, Popper, Gaifman, Scott & Krauss, Fenstad, Miller, David Lewis, Stalnaker, Hintikka or Suppes, to name a few). The resulting theory, to be distinguished from the many-valued-Logics tradition, is strongly reminiscent, in its the mathematical treatment, of Probability theory, though it remains in spirit firmly inside pure Logic.
2007-03-02T19:33:19ZSales Porta, TonLogic and Probability, as theories, have been developed quite independently and, with a few exceptions (like Boole's), have largely ignored each other. And nevertheless they share a lot of similarities, as well a considerable common ground. The exploration of the shared concepts and their mathematical treatment and unification is here attempted following the lead of illustrious researchers (Reichenbach, Carnap, Popper, Gaifman, Scott & Krauss, Fenstad, Miller, David Lewis, Stalnaker, Hintikka or Suppes, to name a few). The resulting theory, to be distinguished from the many-valued-Logics tradition, is strongly reminiscent, in its the mathematical treatment, of Probability theory, though it remains in spirit firmly inside pure Logic.