Narrow Results

This paper addresses the dilation problem on (dual) frames for Krein spaces. We characterize Riesz bases for Krein spaces and equivalence ($(J_1,J_2)$-unitary equivalence) between frames for Krein spaces; prove that every frame (dual frame pair) for a Krein space can be dilated to a Riesz basis (dual Riesz basis pair) for a larger Krein space, and that the corresponding $J$-orthogonal complementary frame ($J$-joint complementary frame) is unique up to equivalence ($(J_1,J_2)$-joint equivalence). Also we illustrate that two equivalent Parseval frames for Krein spaces need not be $(J_1,J_2)$-unitarily equivalent and that not every Parseval frame can be dilated to a $J$-orthonormal basis for a larger Krein space, and derive a result on matrices of finite size as application.

In this paper, we will take a further look at a generalized perceptron-like learning rule which uses dilation and translation parameters in order to enhance the recall performance of higher order Hopfield neural networks without significantly increasing their complexity. We will practically study the influence of these parameters on the perceptron learning and recall process, using a generalized version of the Hebbian learning rule for initialization. Our analysis will be based on a pattern recognition problem with random patterns. We will see that in case of a highly correlated set of patterns, there can be gained some improvements concerning the learning and recall performance. On the other hand, we will show that the dilation and translation parameters have to be chosen carefully for a positive result.

Graph embedding is an important technique that maps a logical graph into a host graph, usually an interconnection network. In this paper, we compute the exact wirelength of embedding Christmas trees into trees. Moreover, we present an algorithm for embedding Christmas trees into caterpillars with dilation 3 proving that the lower bound obtained in [30] is sharp. Further, we solve the maximum subgraph problem for Christmas trees and provide a linear time algorithm to compute the exact wirelength of embedding Christmas trees into trees.

The relationship between local Weyl scaling invariant models and local dilatation invariant actions is critically scrutinized. While actions invariant under local Weyl scalings can be constructed in a straightforward manner, actions invariant under local dilatation transformations can only be achieved in a very restrictive case. The invariant couplings of matter fields to an Abelian vector field carrying a nontrivial scaling weight can be easily built, but an invariant Abelian vector kinetic term can only be realized when the local scale symmetry is spontaneously broken.

In this paper, new operational definitions of binary morphological, both conditional and nonconditional, operations are proposed. The new operations are applied to detect boundary points from binary images. Comparisons of boundary detection algorithms using proposed, standard morphological, and gradient-based operations, showing the effectiveness of the proposed operations, are given. Comparative hardware implementations of standard and proposed morphological operations are also given. Main distinguishing aspects of the new operations are: speed and low hardware implementation (i.e., e.g., low number of buffers and D-Flip–Flops).

This paper shows how mathematical morphological operators can be applied to computer go. On the one hand, mathematical morphology is a very powerful tool within image processing community. On the other hand, the Zobrist's model is well known within the computer go community for its "influence" recognition. We present a model, derived from the closing operator of mathematical morphology and from the Zobrist's model, which yields very good results for "territory" recognition. Moreover, we give efficient implementations of the dilation operator and territory recognition for computer go. This model was found when developing Indigo, our go playing program, and is now used with success in GnuGo, the go playing program of the Free Software Foundation.

The umbra transform serves as a connection between gray-scale morphology and the classical two-valued morphology of G. Matheron and H. Hadwiger. From a general set-theoretic perspective, the umbra transform of an image (or signal) results in an infinite set, even in the discrete case. By employing bound matrix image representation it is possible to represent the umbra by a finite data structure, the result being an approach that is both intuitive and computational. Moreover, the method is essentially dimensionally independent and thus applies to both morphological image and signal processing.

Underground mining has become a viable alternative method for ore extraction when the operation cost of an open pit mine becomes too high. Its success is based on a good characterization of the rocks flow inside the cave. Kinematic and plasticity models, used in the granular flow description in hoppers, have been adapted to describe the experimental situations aimed at sketching the mine operation. The local packing changes that occur at the early stages of rock motion that significantly affect the flow are considered by introducing a dilation front propagating upward. The dynamics of the dilation front limits the extent of the flow generated by the drawing process allowing the assessment of the loosening zone. Based on the linear character of the kinematic model, it is shown that the loosening zone resulting from the simultaneous extraction at two adjacent draw points is accurately described by the dilation front approach.

Let S be a set of points in the plane. What is the minimum possible dilation of all plane graphs that contain S? Even for a set S as simple as five points evenly placed on the circle, this question seems hard to answer; it is not even clear if there exists a lower bound > 1. In this paper we provide the first upper and lower bounds for the embedding problem.

1. Each finite point set can be embedded into the vertex set of a finite triangulation of dilation ≤ 1.1247.

2. Each embedding of a closed convex curve has dilation ≥ 1.00157.

3. Let P be the plane graph that results from intersecting n infinite families of equidistant, parallel lines in general position. Then the vertex set of P has dilation .

Consider a geometric network G in the plane. The dilation between any two vertices x and y in G is the ratio of the shortest path distance between x and y in G to the Euclidean distance between them. The maximum dilation over all pairs of vertices in G is called the dilation of G. In this paper, a randomized algorithm is presented which, when given a polygonal cycle C on n vertices in the plane, computes in O(n log³ n) expected time, the edge of C whose removal results in a polygonal path of smallest possible dilation. It is also shown that the edge whose removal gives a polygonal path of largest possible dilation can be computed in O(n log n) time. If C is a convex polygon, the running time for the latter problem becomes O(n). Finally, it is shown that a (1 - ϵ)-approximation to the dilation of every path C \{e}, for all edges e of C, can be computed in O(n log n) total time.

We prove that computing a geometric minimum-dilation graph on a given set of points in the plane, using not more than a given number of edges, is an NP-hard problem, no matter if edge crossings are allowed or forbidden. We also show that the problem remains NP-hard even when a minimum-dilation tour or path is sought; not even an FPTAS exists in this case.

We study a problem about shortest paths in Delaunay triangulations. Given two nodes s, t in the Delaunay triangulation of a point set S, we look for a new point p ∉ S that can be added, such that the shortest path from s to t, in the Delaunay triangulation of S∪{p}, improves as much as possible. We study several properties of the problem, and give efficient algorithms to find such a point when the graph-distance used is Euclidean and for the link-distance. Several other variations of the problem are also discussed.

The stretch factor and maximum detour of a graph G embedded in a metric space measure how well G approximates the minimum complete graph containing G and the metric space, respectively. In this paper we show that computing the stretch factor of a rectilinear path in L₁ plane has a lower bound of Ω(n log n) in the algebraic computation tree model and describe a worst-case O(σn log² n) time algorithm for computing the stretch factor or maximum detour of a path embedded in the plane with a weighted fixed orientation metric defined by σ ≥ 2 vectors and a worst-case O(n log^d n) time algorithm to d ≥ 3 dimensions in L₁-metric. We generalize the algorithms to compute the stretch factor or maximum detour of trees and cycles in O(σn log^d+1 n) time. We also obtain an optimal O(n) time algorithm for computing the maximum detour of a monotone rectilinear path in L₁ plane.

Given a set S of points in the plane, a geometric network for S is a graph G with vertex set S and straight edges. We consider a broadcasting situation, where one point r ∊ S is a designated source. Given a dilation factor δ, we ask for a geometric network G such that for every point v ∊ S there is a path from r to v in G of length at most δ|rv|, and such that the total edge length is minimized. We show that finding such a network of minimum total edge length is NP-hard, and give an approximation algorithm.

Delaunay and Gabriel graphs are widely studied geometric proximity structures. Motivated by applications in wireless routing, relaxed versions of these graphs known as Locally Delaunay Graphs (LDGs) and Locally Gabriel Graphs (LGGs) were proposed. We propose another generalization of LGGs called Generalized Locally Gabriel Graphs (GLGGs) in the context when certain edges are forbidden in the graph. Unlike a Gabriel Graph, there is no unique LGG or GLGG for a given point set because no edge is necessarily included or excluded. This property allows us to choose an LGG/GLGG that optimizes a parameter of interest in the graph. We show that computing an edge maximum GLGG for a given problem instance is NP-hard and also APX-hard. We also show that computing an LGG on a given point set with dilation ≤ k is NP-hard. Finally, we give an algorithm to verify whether a given geometric graph G = (V,E) is a valid LGG.

We derive a new analytic solution of (n + 1)-dimensional (n ≥ 4) Brans–Dicke–Maxwell theory in the presence of a potential for the scalar field, by applying a conformal transformation to the dilaton gravity theory. Such solutions describe topological charged black holes with unusual asymptotics. We obtain the conserved and thermodynamic quantities through the use of the Euclidean action method. We also study the thermodynamics of the solutions and verify that the conserved and thermodynamic quantities of the solutions satisfy the first law of black hole thermodynamics.

Mini superspace cosmology treats the scale factor a(t), the lapse function n(t) and an optional dilation field ϕ(t) as canonical variables. While pre-fixing n(t) means losing the Hamiltonian constraint, pre-fixing a(t) is serendipitously harmless at this level. This suggests an alternative to the Hartle–Hawking approach, where the pre-fixed a(t) and its derivatives are treated as explicit functions of time, leaving n(t) and a now mandatory ϕ(t) to serve as canonical variables. The naive gauge pre-fix a(t) = const. is clearly forbidden, causing evolution to freeze altogether; so pre-fixing the scale factor, say a(t) = t, necessarily introduces explicit time dependence into the Lagrangian. Invoking Dirac's prescription for dealing with constraints, we construct the corresponding mini superspace time-dependent total Hamiltonian and calculate the Dirac brackets, characterized by {n, ϕ}_D ≠ 0, which are promoted to commutation relations in the quantum theory.

The phase diagram of quantum chromodynamics is conjectured to have a rich structure containing at least three forms of matter: hadronic nuclear matter, quarkyonic matter and quark–gluon plasma. We justify the origin of the quarkyonic phase transition in a chiral-quark model and describe its formulation in terms of Skyrme crystals.

The branching structure of neurones is thought to influence patterns of connectivity and how inputs are integrated within the arbor. Recent studies have revealed a remarkable degree of variation in the branching structure of pyramidal cells in the cerebral cortex of diurnal primates, suggesting regional specialization in neuronal function. Such specialization in pyramidal cell structure may be important for various aspects of visual function, such as object recognition and color processing. To better understand the functional role of regional variation in the pyramidal cell phenotype in visual processing, we determined the complexity of the dendritic branching pattern of pyramidal cells in visual cortex of the nocturnal New World owl monkey. We used the fractal dilation method to quantify the branching structure of pyramidal cells in the primary visual area (V1), the second visual area (V2) and the caudal and rostral subdivisions of inferotemporal cortex (ITc and ITr, respectively), which are often associated with color processing. We found that, as in diurnal monkeys, there was a trend for cells of increasing fractal dimension with progression through these cortical areas. The increasing complexity paralleled a trend for increasing symmetry. That we found a similar trend in both diurnal and nocturnal monkeys suggests that it was a feature of a common anthropoid ancestor.

Previously it has been shown that the branching pattern of pyramidal cells varies markedly between different cortical areas in simian primates. These differences are thought to influence the functional complexity of the cells. In particular, there is a progressive increase in the fractal dimension of pyramidal cells with anterior progression through cortical areas in the occipitotemporal (OT) visual stream, including the primary visual area (V1), the second visual area (V2), the dorsolateral area (DL, corresponding to the fourth visual area) and inferotemporal cortex (IT). However, there are as yet no data on the fractal dimension of these neurons in prosimian primates. Here we focused on the nocturnal prosimian galago (Otolemur garnetti). The fractal dimension (D), and aspect ratio (a measure of branching symmetry), was determined for 111 layer III pyramidal cells in V1, V2, DL and IT. We found, as in simian primates, that the fractal dimension of neurons increased with anterior progression from V1 through V2, DL, and IT. Two important conclusions can be drawn from these results: (1) the trend for increasing branching complexity with anterior progression through OT areas was likely to be present in a common primate ancestor, and (2) specialization in neuron structure more likely facilitates object recognition than spectral processing.