Search results for "Graph theory"
showing 10 items of 784 documents
On the Consistency of Non-Stationary Multipath Fading Channels with Respect to the Average Doppler Shift and the Doppler Spread
2017
This paper is concerned with the consistency of non-stationary multipath fading channels. We introduce conditions under which a channel model is consistent w.r.t. the average Doppler shift and the Doppler spread. The conditions are applied to two classes of non-stationary channel models. The first class, which is termed Class A, is characterized by channel models based on an integral relationship between the path phases and the associated time-variant Doppler frequencies. The second class of models, called the Class B models, emerges from standard sum-of-cisoids (SOC) models by replacing the time-independent Doppler frequencies by time-dependent Doppler frequencies. It is shown that the Cla…
Topology of correlation-based minimal spanning trees in real and model markets
2003
We present here a topological characterization of the minimal spanning tree that can be obtained by considering the price return correlations of stocks traded in a financial market. We compare the minimal spanning tree obtained from a large group of stocks traded at the New York Stock Exchange during a 12-year trading period with the one obtained from surrogated data simulated by using simple market models. We find that the empirical tree has features of a complex network that cannot be reproduced, even as a first approximation, by a random market model and by the one-factor model.
Improved SOM Learning using Simulated Annealing
2007
Self-Organizing Map (SOM) algorithm has been extensively used for analysis and classification problems. For this kind of problems, datasets become more and more large and it is necessary to speed up the SOM learning. In this paper we present an application of the Simulated Annealing (SA) procedure to the SOM learning algorithm. The goal of the algorithm is to obtain fast learning and better performance in terms of matching of input data and regularity of the obtained map. An advantage of the proposed technique is that it preserves the simplicity of the basic algorithm. Several tests, carried out on different large datasets, demonstrate the effectiveness of the proposed algorithm in comparis…
Path to Overcome Material and Fundamental Obstacles in Spin Valves Based on MoS2 and Other Transition-Metal Dichalcogenides
2019
The recent introduction of two-dimensional materials into magnetic tunnel junctions (2D MTJs) offers very promising properties for spintronics, such as atomically defined interfaces, spin filtering, perpendicular anisotropy, and modulation of spin-orbit torque. Nevertheless, the difficulty of integrating exfoliated 2D materials into spintronic devices has limited exploration. Here the authors find a fabrication process leading to superior performance in MTJs based on transition-metal dichalcogenides, and further suggest a path to alleviate basic issues of technology and physics for 2D MTJs.
Radio k-Labelings for Cartesian Products of Graphs
2005
International audience; Frequency planning consists in allocating frequencies to the transmitters of a cellular network so as to ensure that no pair of transmitters interfere. We study the problem of reducing interference by modeling this by a radio k-labeling problem on graphs: For a graph G and an integer k ≥ 1, a radio k-labeling of G is an assignment f of non negative integers to the vertices of G such that |f(x)−f(y)| ≥ k+1−dG(x,y), for any two vertices x and y, where dG(x,y) is the distance between x and y in G. The radio k-chromatic number is the minimum of max{f(x)−f(y):x,y ∈ V(G)} over all radio k-labelings f of G. In this paper we present the radio k-labeling for the Cartesian pro…
Joint Graph Learning and Signal Recovery via Kalman Filter for Multivariate Auto-Regressive Processes
2018
In this paper, an adaptive Kalman filter algorithm is proposed for simultaneous graph topology learning and graph signal recovery from noisy time series. Each time series corresponds to one node of the graph and underlying graph edges express the causality among nodes. We assume that graph signals are generated via a multivariate auto-regressive processes (MAR), generated by an innovation noise and graph weight matrices. Then we relate the state transition matrix of Kalman filter to the graph weight matrices since both of them can play the role of signal propagation and transition. Our proposed Kalman filter for MAR processes, called KF-MAR, runs three main steps; prediction, update, and le…
Pruning Incremental Linear Model Trees with Approximate Lookahead
2014
Incremental linear model trees with approximate lookahead are fast, but produce overly large trees. This is due to non-optimal splitting decisions boosted by a possibly unlimited number of examples obtained from a data source. To keep the processing speed high and the tree complexity low, appropriate incremental pruning techniques are needed. In this paper, we introduce a pruning technique for the class of incremental linear model trees with approximate lookahead on stationary data sources. Experimental results show that the advantage of approximate lookahead in terms of processing speed can be further improved by producing much smaller and consequently more explanatory, less memory consumi…
Hierarchical Structure in Financial Markets
1998
I find a topological arrangement of stocks traded in a financial market which has associated a meaningful economic taxonomy. The topological space is a graph connecting the stocks of the portfolio analyzed. The graph is obtained starting from the matrix of correlation coefficient computed between all pairs of stocks of the portfolio by considering the synchronous time evolution of the difference of the logarithm of daily stock price. The hierarchical tree of the subdominant ultrametric space associated with the graph provides information useful to investigate the number and nature of the common economic factors affecting the time evolution of logarithm of price of well defined groups of sto…
Modeling Forest Tree Data Using Sequential Spatial Point Processes
2021
AbstractThe spatial structure of a forest stand is typically modeled by spatial point process models. Motivated by aerial forest inventories and forest dynamics in general, we propose a sequential spatial approach for modeling forest data. Such an approach is better justified than a static point process model in describing the long-term dependence among the spatial location of trees in a forest and the locations of detected trees in aerial forest inventories. Tree size can be used as a surrogate for the unknown tree age when determining the order in which trees have emerged or are observed on an aerial image. Sequential spatial point processes differ from spatial point processes in that the…
Binary distributions of concentric rings
2014
We introduce families of jointly symmetric, binary distributions that are generated over directed star graphs whose nodes represent variables and whose edges indicate positive dependences. The families are parametrized in terms of a single parameter. It is an outstanding feature of these distributions that joint probabilities relate to evenly spaced concentric rings. Kronecker product characterizations make them computationally attractive for a large number of variables. We study the behavior of different measures of dependence and derive maximum likelihood estimates when all nodes are observed and when the inner node is hidden.