Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Roberto P. J. Perazzo"'
Publikováno v:
Physica A: Statistical Mechanics and its Applications. 337:635-644
We discuss a modification of the Evolutionary Minority Game (EMG) in which agents are placed in the nodes of a regular or a random graph. A neighborhood for each agent can thus be defined and a modification of the usual relaxation dynamics can be mad
Publikováno v:
Advances in Complex Systems. :21-38
We study the dynamics of self-organized systems when disturbed by shocks. For this purpose, we consider extensions of the "Bar Attendance Model" [1] (BAM), which provides a stylized setting for the analysis of the emergence of coordination in the beh
Publikováno v:
Neural Processing Letters. 16:243-257
A neural network model of associative memory is presented which unifies the two historically more relevant enhancements to the basic Little-Hopfield discrete model: the graded response units approach and the stochastic, Glauber-inspired model with a
This paper studies Bertrand price-setting behavior when firms face capacity constraints (Bertrand–Edgeworth game). This game is known to lack equilibria in pure strategies, while the mixed-strategy equilibria are hard to characterize. We explore fa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::adc58f9c56657b5c06ff66cc19cb45e9
http://www.sciencedirect.com/science/article/pii/S0167268114001401
http://www.sciencedirect.com/science/article/pii/S0167268114001401
Publikováno v:
Neural Processing Letters. 12:129-144
A generalization of the Little–Hopfield neural network model for associative memories is presented that considers the case of a continuum of processing units. The state space corresponds to an infinite dimensional euclidean space. A dynamics is pro
Publikováno v:
Complexity. 2:54-60
Autor:
Hernán A. Makse, Roberto P. J. Perazzo
Publikováno v:
International Journal of Neural Systems. :351-360
The dyslexic behaviour of a layered network is interpreted as arising from its incomplete training using a cost function that is sensitive to the grouping of Boolean functions into symmetry classes. The training is envisaged as a simulated annealing
Publikováno v:
International Journal of Neural Systems. :237-245
A model is proposed in which the synaptic efficacies of a feedforward neural network are adapted with a cost function that vanishes if the boolean function that is represented has the same symmetry properties as the target one. The function chosen ac
Autor:
A. R. Schuschny, Roberto P. J. Perazzo
Publikováno v:
International journal of neural systems. 7(1)
We propose a Boolean cellular automaton to model an artificial adaptive living organism in order to investigate the development of cyclic vital functions during a simulated evolutionary process. The organism is endowed with a basic architecture consi
We describe an array of quantum gates implementing Shor's algorithm for prime factorization in a quantum computer. The array includes a circuit for modular exponentiation with several subcomponents (such as controlled multipliers, adders, etc) which
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4728a3e3feef6ac50655e48d19d8af35
http://arxiv.org/abs/quant-ph/9601021
http://arxiv.org/abs/quant-ph/9601021