搜索结果: 1-13 共查到“统计学其他学科 networks”相关记录13条 . 查询时间(0.078 秒)
Fractal-driven distortion of resting state functional networks in fMRI: a simulation study
Fractal-driven distortion resting state functional networks simulation study
2012/9/17
Fractals are self-similar and scale-invariant patterns found ubiquitously in nature. A lot of evidences implying fractal properties such as 1/f power spectrums have been also observed in resting state...
On computation of clustering coefficient in a class of random networks
random graph clustering degree of separation
2012/9/18
The random networks enriched with additional structures asmetric and group-symmetry in background metric space are investigated. The important quantities like he clustering coefficient as well as the ...
Near-Optimal Node Blacklisting in Adversarial Networks
Near-Optimal Node Blacklisting Adversarial Networks
2012/9/18
Many communication networks contain nodes which may misbehave, thus incurring a cost to the network operator. Weconsider the problem of how to manage the nodes when the operator receives a payoff for ...
Reverse Engineering Gene Interaction Networks Using the Phi-Mixing Coefficient
Reverse Engineering Gene Interaction Networks Phi-Mixing Coefficient
2012/9/18
In this paper, we present a new algorithm for reverse-engineering gene interaction networks (GINs) from expression data, by viewing the expres-sion levels of various genes as coupled random variables....
Reverse Engineering Gene Interaction Networks Using the Phi-Mixing Coefficient
Reverse Engineering Gene Interaction Networks Phi-Mixing Coefficient
2012/9/18
In this paper, we present a new algorithm for reverse-engineering gene interaction networks (GINs) from expression data, by viewing the expres-sion levels of various genes as coupled random variables....
Statistical Inference of Allopolyploid Species Networks in the Presence of Incomplete Lineage Sorting
Allopolyploid hybridization Bayesian phylogenetics network
2012/9/18
Polyploidy is an important speciation mechanism, particularly in land plants. Allopolyploid species are formed after hybridization betweenother-wise intersterile parental species. Recent theoretical p...
Discriminating different classes of biological networks by analyzing the graphs spectra distribution
Discriminating different classes biological networks analyzing the graphs spectra distribution
2012/9/17
The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of com-plex networks, such as highly connected...
Balancing Lifetime and Classification Accuracy of Wireless Sensor Networks
Balancing Lifetime Classification Accuracy Wireless Sensor Networks
2012/9/18
Wireless sensor networks are composed of dis-tributed sensors that can be used for signal detection or classification. The likelihood functions of the hypotheses are often not known in advance, and de...
Sequential detection of multiple change points in networks: a graphical model approach
Sequential detection of multiple change points in networks graphical model approach
2012/9/19
We propose a probabilistic formulation that enables sequential detection of multiple change points in a network setting. We present a class of sequential detection rules for cer-tain functionals of ch...
Robust Bayesian inference of networks using Dirichlet t-distributions
Bayesian inference Dirichlet process graphical model Markov chain Monte Carlo t-distribution.
2012/9/18
Bayesian graphical modeling provides an appealing way to obtain uncertainty esti-mates when inferring network structures, and much recent progress has been made for Gaussian models. These models have ...
Majority Dynamics and Aggregation of Information in Social Networks
Majority Dynamics Aggregation of Information Social Networks
2012/9/18
Considernindividuals who, by popular vote, choose among q≥2 alternatives, one of which is “better” than the others. Assume that each individual votes independently at random, and that the probability ...
Model-Based Clustering of Large Networks
social networks stochastic block models finite mixture models EM algorithms generalized EM algorithms variational EM algorithms MM algorithms
2012/9/18
We describe a network clustering framework, based on finite mix-ture models, that can be applied to discrete-valued networks with hundreds of thousands of nodes and billions of edge variables. Rela-ti...
Large information plus noise random matrix models and consistent subspace estimation in large sensor networks
Large information plus noise random matrix models consistent subspace estimation large sensor networks
2011/7/7
In array processing, a common problem is to estimate the angles of arrival of $K$ deterministic sources impinging on an array of $M$ antennas, from $N$ observations of the source signal, corrupted by ...