We develop a neural network formulation for multi-vehicle navigation on a twodimensional surface. here. A time-linking map is generated for each individual vehicle using techniques similar to the known shortest path a...
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The problem of tracking multiple targets in the presence of displacement noise and clutter is formulated as a nonconvex optimization problem. The form of the suggested cost function is shown to be suitable for the Gra...
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A two vehicle navigator on a descrete space is analyzed. The concept of linking time maps as source to optimal path planning is discussed. The rules for constructing these map are given in a cellular automata mode. Th...
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We describe how explicit domain decomposition can lead to implementations of large scale scientific applications which run with near optimal performance on concurrent supercomputers with a variety of architectures. In...
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The Monte Carlo simulation of a model polymer is implemented on the Mark111 Hypercube computer under the CROS operating system. The polymer model and the simulation method are discussed. The key features of the implem...
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A new numerical approach by Furmanski and Kolawa to quantum chromodynamics is based on *** the underlying Hamiltonian. This method involves the generation of states by repeated action of a potential operator. This sym...
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We develop a neural network formulation for multi-vehicle navigation on a two-dimensional surface, here. A time-linking map is generated for each individual vehicle using techniques similar to the known shortest path ...
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An approach to distributed memory parallel programming that has recently become popular is one where the programmer explicitly specifies the data decomposition using language extensions, and a, compiler generates all ...
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We have measured the dynamical critical exponent z for the Swendsen-Wang and the Wolff cluster update algorithms, as well as a number of variants of these algorithms, for the q=2 and q=3 Potts models in two dimensions...
We have measured the dynamical critical exponent z for the Swendsen-Wang and the Wolff cluster update algorithms, as well as a number of variants of these algorithms, for the q=2 and q=3 Potts models in two dimensions. We find that although the autocorrelation times differ considerably between algorithms, the critical exponents are the same. For q=2, we find that although the data are better fitted by a logarithmic increase in the autocorrelation time with lattice size, they are also consistent with a power law with exponent z≊0.25, especially if there are non-negligible corrections to scaling.
A new approach to clustering based on statistical physics is presented. The problem is formulated as fuzzy clustering and the association probability distribution is obtained by maximizing the entropy at a given avera...
A new approach to clustering based on statistical physics is presented. The problem is formulated as fuzzy clustering and the association probability distribution is obtained by maximizing the entropy at a given average variance. The corresponding Lagrange multiplier is related to the ‘‘temperature’’ and motivates a deterministic annealing process where the free energy is minimized at each temperature. Critical temperatures are derived for phase transitions when existing clusters split. It is a hierarchical clustering estimating the most probable cluster parameters at various average variances.
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