Using models to model-check recursive schemes

We propose a model-based approach to the model checking problem for recursive schemes. Since simply typed lambda calculus with the fixpoint operator, lambda-Y-calculus, is equivalent to schemes, we propose the use of a model of lambda-Y-calculus to discriminate the terms that satisfy a given property. If a model is finite in every type, this gives a decision procedure. We provide a construction of such a model for every property expressed by automata with trivial acceptance conditions and divergence testing. Such properties pose already interesting challenges for model construction. Moreover, we argue that having models capturing some class of properties has several other virtues in addition to providing decidability of the model-checking problem. As an illustration, we show a very simple construction transforming a scheme to a scheme reflecting a property captured by a given model.Comment: Long version of a paper presented at TLCA 201

Generalized gamma approximation with rates for urns, walks and trees

We study a new class of time inhomogeneous P\'olya-type urn schemes and give optimal rates of convergence for the distribution of the properly scaled number of balls of a given color to nearly the full class of generalized gamma distributions with integer parameters, a class which includes the Rayleigh, half-normal and gamma distributions. Our main tool is Stein's method combined with characterizing the generalized gamma limiting distributions as fixed points of distributional transformations related to the equilibrium distributional transformation from renewal theory. We identify special cases of these urn models in recursive constructions of random walk paths and trees, yielding rates of convergence for local time and height statistics of simple random walk paths, as well as for the size of random subtrees of uniformly random binary and plane trees.Comment: Published at http://dx.doi.org/10.1214/15-AOP1010 in the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org

Recursive Alterations of the Relationship between Simple Membrane Geometry and Insertion of Amphiphilic Motifs

The shape and composition of a membrane directly regulate the localization, activity, and signaling properties of membrane associated proteins. Proteins that both sense and generate membrane curvature, e.g., through amphiphilic insertion motifs, potentially engage in recursive binding dynamics, where the recruitment of the protein itself changes the properties of the membrane substrate. Simple geometric models of membrane curvature interactions already provide prediction tools for experimental observations, however these models are treating curvature sensing and generation as separated phenomena. Here, we outline a model that applies both geometric and basic thermodynamic considerations. This model allows us to predict the consequences of recursive properties in such interaction schemes and thereby integrate the membrane as a dynamic substrate. We use this combined model to hypothesize the origin and properties of tubular carrier systems observed in cells. Furthermore, we pinpoint the coupling to a membrane reservoir as a factor that influences the membrane curvature sensing and generation properties of local curvatures in the cell in line with classic determinants such as lipid composition and membrane geometry

Models, Statistics, and Rates of Binary Correlated Sources

This paper discusses and analyzes various models of binary correlated sources, which may be relevant in several distributed communication scenarios. These models are statistically characterized in terms of joint Probability Mass Function (PMF) and covariance. Closed-form expressions for the joint entropy of the sources are also presented. The asymptotic entropy rate for very large number of sources is shown to converge to a common limit for all the considered models. This fact generalizes recent results on the information-theoretic performance limit of communication schemes which exploit the correlation among sources at the receiver.Comment: submitted for publicatio

A New Recursive Least-Squares Method with Multiple Forgetting Schemes

We propose a recursive least-squares method with multiple forgetting schemes to track time-varying model parameters which change with different rates. Our approach hinges on the reformulation of the classic recursive least-squares with forgetting scheme as a regularized least squares problem. A simulation study shows the effectiveness of the proposed method