151 resultados para Gradient bifurcation problem


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A method is given for solving an optimal H2 approximation problem for SISO linear time-invariant stable systems. The method, based on constructive algebra, guarantees that the global optimum is found; it does not involve any gradient-based search, and hence avoids the usual problems of local minima. We examine mostly the case when the model order is reduced by one, and when the original system has distinct poles. This case exhibits special structure which allows us to provide a complete solution. The problem is converted into linear algebra by exhibiting a finite-dimensional basis for a certain space, and can then be solved by eigenvalue calculations, following the methods developed by Stetter and Moeller. The use of Buchberger's algorithm is avoided by writing the first-order optimality conditions in a special form, from which a Groebner basis is immediately available. Compared with our previous work the method presented here has much smaller time and memory requirements, and can therefore be applied to systems of significantly higher McMillan degree. In addition, some hypotheses which were required in the previous work have been removed. Some examples are included.

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An analytical solution is presented for the vertical consolidation of a cylindrical annulus of clay with horizontal drainage occurring to concentric internal and external drainage boundaries. Numerical results are given for various ratios of internal and external radii and it is shown that solutions for conventional one-dimensional consolidation, and for consolidation of a cylindrical block of clay with drainage only to the outer cylindrical boundary form extremes to the analysis presented here. An application of the solution to the estimation of horizontal permeability of clay is briefly described.

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Rigid retaining walls are considered. Both the backfill and the soil supporting the foundation of the model wall have been made of a single dry granular soil. Attention is limited to one grain.

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We present a gradient-based motion capture system that robustly tracks a human hand, based on abstracted visual information - silhouettes. Despite the ambiguity in the visual data and despite the vulnerability of gradient-based methods in the face of such ambiguity, we minimise problems related to misfit by using a model of the hand's physiology, which is entirely non-visual, subject-invariant, and assumed to be known a priori. By modelling seven distinct aspects of the hand's physiology we derive prior densities which are incorporated into the tracking system within a Bayesian framework. We demonstrate how the posterior is formed, and how our formulation leads to the extraction of the maximum a posteriori estimate using a gradient-based search. Our results demonstrate an enormous improvement in tracking precision and reliability, while also achieving near real-time performance. © 2009 IEEE.

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The scattering of sound from a point source by a Rankine vortex is investigated numerically by solving the Euler equations with the novel high-resolution CABARET method. For several Mach numbers of the vortex, the time-average amplitudes of the scattered field obtained from the numerical modeling are compared with the theoretical scaling laws' predictions. Copyright © 2009 by Sergey Karabasov.

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Experiments were conducted investigating the interaction between a normal shock wave and a corner boundary layer in a constant area rectangular duct. Active corner suction and passive blowing were applied to manipulate the natural corner flows developing in the working section of the Cambridge University supersonic wind tunnel. In addition robust vane micro-vortex generators were applied to the corners of the working section. Experiments were conducted at Mach numbers of M∞=1.4 and 1.5. Flow visualisation was carried out through schlieren and surface oil flow, while static pressures were recorded via floor tappings. The results indicate that an interplay occurs between the corner flow and the centre line flow. It is believed that corner flow separation acts to induce a shock bifurcation, which in turn leads to a smearing of the adverse pressure gradient elsewhere. In addition the blockage effect from the corners was seen to result in a reacceleration of the subsonic post-shock flow. As a result manipulation of the corner regions allows a separated or attached centre line flow to be observed at the same Mach number. Copyright © 2010 by Babinsky, Burton, Bruce.

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This article presents a novel algorithm for learning parameters in statistical dialogue systems which are modeled as Partially Observable Markov Decision Processes (POMDPs). The three main components of a POMDP dialogue manager are a dialogue model representing dialogue state information; a policy that selects the system's responses based on the inferred state; and a reward function that specifies the desired behavior of the system. Ideally both the model parameters and the policy would be designed to maximize the cumulative reward. However, while there are many techniques available for learning the optimal policy, no good ways of learning the optimal model parameters that scale to real-world dialogue systems have been found yet. The presented algorithm, called the Natural Actor and Belief Critic (NABC), is a policy gradient method that offers a solution to this problem. Based on observed rewards, the algorithm estimates the natural gradient of the expected cumulative reward. The resulting gradient is then used to adapt both the prior distribution of the dialogue model parameters and the policy parameters. In addition, the article presents a variant of the NABC algorithm, called the Natural Belief Critic (NBC), which assumes that the policy is fixed and only the model parameters need to be estimated. The algorithms are evaluated on a spoken dialogue system in the tourist information domain. The experiments show that model parameters estimated to maximize the expected cumulative reward result in significantly improved performance compared to the baseline hand-crafted model parameters. The algorithms are also compared to optimization techniques using plain gradients and state-of-the-art random search algorithms. In all cases, the algorithms based on the natural gradient work significantly better. © 2011 ACM.

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