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Existence and uniqueness of solutions for non-linear stochastic partial differential equations.

Tomás Caraballo Garrido — 1991

Collectanea Mathematica

We state some results on existence and uniqueness for the solution of non linear stochastic PDEs with deviating arguments. In fact, we consider the equation dx(t) + (A(t,x(t)) + B(t,x(a(t))) + f(t)dt = (C(t,x(b(t)) + g(t))dwt, where A(t,·), B(t,·) and C(t,·) are suitable families of non linear operators in Hilbert spaces, wt is a Hilbert valued Wiener process, and a, b are functions of delay. If A satisfies a coercivity condition and a monotonicity hypothesis, and if B, C are Lipschitz continuous,...

Uniform approximation theorems for real-valued continuous functions.

M. Isabel GarridoFrancisco Montalvo — 1991

Extracta Mathematicae

For a completely regular space X, C(X) and C*(X) denote, respectively, the algebra of all real-valued continuous functions and bounded real-valued continuous functions over X. When X is not a pseudocompact space, i.e., if C*(X) ≠ C(X), theorems about uniform density for subsets of C*(X) are not directly translatable to C(X). In [1], Anderson gives a sufficient condition in order for certain rings of C(X) to be uniformly dense, but this condition is not necessary. In this paper we study...

On some generalizations of the Kakutani-Stone and Stone-Weierstrass theorems.

M. Isabel GarridoFrancisco Montalvo — 1991

Extracta Mathematicae

For a completely regular space X, C*(X) denotes the algebra of all bounded real-valued continuous functions over X. We consider the topology of uniform convergence over C*(X). When K is a compact space, the Stone-Weierstrass and Kakutani-Stone theorems provide necessary and sufficient conditions under which a function f ∈ C*(K) can be uniformly approximated by members of an algebra, lattice or vector lattice of C*(K). In this way, the uniform closure and, in particular, the uniform density...

Aplicaciones empresariales de data mining.

Lluís GarridoJosé Ignacio Latorre — 2001

Qüestiió

El Data Mining, o extracción de información útil y no evidente de grandes bases de datos, es una tecnología con un gran potencial para ayudar a las empresas a focalizar sus esfuerzos alrededor de la información importante contenida en sus "data warehouses". En este artículo analizaremos las ideas básicas que sustentan el Data Mining y, más concretamente, la utilización de redes neuronales como herramienta estadística avanzada. Presentaremos también dos ejemplos reales de la aplicación...

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