Search results for "ALGORITHM"
showing 10 items of 4887 documents
Dynamic Gaussian Graphical Models for Modelling Genomic Networks
2014
After sequencing the entire DNA for various organisms, the challenge has become understanding the functional interrelatedness of the genome. Only by understanding the pathways for various complex diseases can we begin to make sense of any type of treatment. Unfortunately, decyphering the genomic network structure is an enormous task. Even with a small number of genes the number of possible networks is very large. This problem becomes even more difficult, when we consider dynamical networks. We consider the problem of estimating a sparse dynamic Gaussian graphical model with \(L_1\) penalized maximum likelihood of structured precision matrix. The structure can consist of specific time dynami…
Some Effects of Individual Learning on the Evolution of Sensors
2001
In this paper, we present an abstract model of sensor evolution, where sensor development is only determined by artificial evolution and the adaptation of agent reactions is accomplished by individual learning. With the environment cast into a MDP framework, sensors can be conceived as a map from environmental states to agent observations and Reinforcement Learning algorithms can be utilised. On the basis of a simple gridworld scenario, we present some results of the interaction between individual learning and evolution of sensors.
Aplicación del Estimador de Parámetros de Segmentación por Media-desplazada (EPSM) a las imágenes de satélite de muy alta resolución espacial: Tetuán…
2015
<p>La segmentación de imágenes constituye un paso crucial en el Análisis de Imágenes Basado en Objetos (AIBO). Combinando distintos valores de los parámetros de entrada de los algoritmos de segmentación se obtienen diferentes resultados. En general, los parámetros óptimos seleccionados se determinan mediante interpretación visual; por lo tanto, la definición de las combinaciones óptimas es una tarea considerablemente difícil. En la presente investigación, se propone una herramienta analítica que denominamos Estimador de Parámetros de Segmentación por Media-desplazada (EPSM) aplicada a la selección automatizada de los valores de los parámetros de segmentación en las imágenes de satélit…
Practical Issues on Energy-Growth Nexus Data and Variable Selection With Bayesian Analysis
2018
Abstract Given that the energy-growth nexus (EGN) is short of a complete theoretical base, the production function used therein is typically complemented with numerous variables that characterize an economy. Researchers are often puzzled not only with the selection of variables per se, but also with the variable sources and the various data handlings which become apparent and available only after years of experience in this research field. Thus, this chapter is divided into two distinctive parts: The first part contains an overview of the available data sources for the EGN as well as a succinct selection of advice on data handlings, transformations, and interpretations that could come handy…
On incorporating the paradigms of discretization and Bayesian estimation to create a new family of pursuit learning automata
2013
Published version of an article in the journal: Applied Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/s10489-013-0424-x There are currently two fundamental paradigms that have been used to enhance the convergence speed of Learning Automata (LA). The first involves the concept of utilizing the estimates of the reward probabilities, while the second involves discretizing the probability space in which the LA operates. This paper demonstrates how both of these can be simultaneously utilized, and in particular, by using the family of Bayesian estimates that have been proven to have distinct advantages over their maximum likelihood counterparts. The success of LA-…
Finding Prediction Limits for a Future Number of Failures in the Prescribed Time Interval under Parametric Uncertainty
2012
Computing prediction intervals is an important part of the forecasting process intended to indicate the likely uncertainty in point forecasts. Prediction intervals for future order statistics are widely used for reliability problems and other related problems. In this paper, we present an accurate procedure, called ‘within-sample prediction of order statistics', to obtain prediction limits for the number of failures that will be observed in a future inspection of a sample of units, based only on the results of the first in-service inspection of the same sample. The failure-time of such units is modeled with a two-parameter Weibull distribution indexed by scale and shape parameters β and δ, …
Low-complexity AoA and AoD Estimation in the Transformed Spatial Domain for Millimeter Wave MIMO Channels
2021
High-accuracy angle of arrival (AoA) and angle of departure (AoD) estimation is critical for cell search, stable communications and positioning in millimeter wave (mmWave) cellular systems. Moreover, the design of low-complexity AoA/AoD estimation algorithms is also of major importance in the deployment of practical systems to enable a fast and resource-efficient computation of beamforming weights. Parametric mmWave channel estimation allows to describe the channel matrix as a combination of direction-dependent signal paths, exploiting the sparse characteristics of mmWave channels. In this context, a fast Transformed Spatial Domain Channel Estimation (TSDCE) algorithm was recently proposed …
Clustering-Assisted 3D Beamforming for Throughput Maximization in mmWave Networks
2021
Beamforming schemes have been widely used to improve network throughput in 5G mmWave networks. However, 3D beamforming schemes have hereto not been investigated in this context. In this work, a cluster-assisted 3D beamforming scheme is proposed to optimize the downtilt angle for network coverage and throughput maximization. User Equipment (UEs) are clustered based on inter-user and the inter-cluster distances. The interference is accounted from the adjacent clusters and thus frequency resources can be assigned to the non-adjacent clusters. Optimal downtilt angles are obtained for every cluster to maximize the throughput while considering the interference from adjacent clusters. 3D beam patt…
Coordination in a multi-cell multi-antenna multi-user W-CDMA system: a beamforming approach
2008
The problem of designing joint power control and optimal beamforming (JPCOB) algorithms for the downlink of a coordinated multi-cell WCDMA system is considered throughout this paper. In this case, the JPCOB design is formulated as the problem of minimizing the total transmitted power in the coordinated multi-cell system, subject to a certain quality of service requirement for each user. In this paper, the performance of two JPCOB algorithms based on different beamforming approaches is compared over the coordinated multi-cell system. The first one, obtains local beamformers by means of the well-known virtual uplink-downlink duality. In contrast, the second algorithm implements multi-base bea…
3/4-efficient Bell measurement with passive linear optics and unentangled ancillae
2014
It is well known that an unambiguous discrimination of the four optically encoded Bell states is possible with a probability of $50\%$ at best, when using static, passive linear optics and arbitrarily many vacuum mode ancillae. By adding unentangled single-photon ancillae, we are able to surpass this limit and reach a success probability of at least $75\%$. We discuss the error robustness of the proposed scheme and a generalization to reach a success probability arbitrarily close to $100\%$.