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- Gary L Beck, Mihaela T Matache
- 2008

This study considers a simple Boolean network with N nodes, each node's state at time t being determined by a certain number of parent nodes. The network is analyzed when the connectivity k is fixed or variable. Making use of a Boolean rule that is a generalization of Rule 22 of elementary cellular automata, a generalized formula for providing the… (More)

This paper considers a simple Boolean network with N nodes, each node's state at time t being determined by a certain number k of parent nodes, which is fixed for all nodes. The nodes, with randomly assigned neighborhoods, are updated based on various asynchronous schemes. We make use of a Boolean rule that is a generalization of rule 126 of elementary… (More)

Prediction markets have been shown to be a useful tool in forecasting the outcome of future events by aggregating public opinion about the events' outcome. Previous research on prediction markets has mostly analyzed the prediction markets by building complex analytical models. In this paper, we posit that simpler yet powerful Boolean rules can be used to… (More)

We consider the reproducing kernel Hilbert space H µ induced by a kernel which is obtained using the Fourier-Stieltjes transform of a regular, positive, finite Borel measure µ on a locally compact abelian topological group Γ. Denote by G the dual of Γ. We determine H µ as a certain subspace of the space C 0 (G) of all continuous function on G vanishing at… (More)

- Ray Goodman, Mihaela T Matache
- 2008

This study provides an analysis of the dynamics of fixed-size directed Boolean networks governed by generalizations of elementary cellular au-tomata rules 22 and 126, under a power-law distribution of parent nodes and a popularity parent assignment. The analysis shows the existence of a two-piece chaotic attractor for smaller values of the power-law… (More)

- Naomi Kochi, Tomáš Helikar, Laura Allen, Jim A Rogers, Zhenyuan Wang, Mihaela T Matache
- BMC Systems Biology
- 2014

An algebraic method for information fusion based on nonadditive set functions is used to assess the joint contribution of Boolean network attributes to the sensitivity of the network to individual node mutations. The node attributes or characteristics under consideration are: in-degree, out-degree, minimum and average path lengths, bias, average sensitivity… (More)

In this paper we generate upper and lower bounds for the sensitivity to noise of a Boolean function using relaxed assumptions on input choices and noise. The robustness of a Boolean network to noisy inputs is related to the average sensitivity of that function. The average sensitivity measures how sensitive to changes in the inputs the output of the… (More)

Boolean networks have been widely used as models for gene regulatory networks, signal transduction networks, or neural networks, among many others. One of the main difficulties in analyzing the dynamics of a Boolean network and its sensitivity to perturbations or mutations is the fact that it grows exponentially with the number of nodes. Therefore, various… (More)

In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: a b s t r a c t The problem formulated in the title is investigated. The case of… (More)

A multiple Fractional Brownian Motion (FBM) based traffic model of the following form is considered A(t) = mt + M j=1 σ j B Hj (t) + τ W (t). Here B H j (t) are independent FBMs with Hurst parameters 1/2 < H j < 1 and W (t) is a Brownian Motion independent of the FBMs. Various lower bounds for the overflow probability of the associated queuing system are… (More)