Search Results for "state-thread"

A package for transient and steady state simulation of organic solar cells.

This toolbox is used to generate finite abstractions of autonomous Max-Plus-Linear (MPL) systems over R^n. Abstractions are characterized as finite-state Labeled Transition Systems (LTS). The LTS finite abstractions are shown to either simulate or to bisimulate the original MPL system. LTS models are to be verified against given specifications expressed as formulae in Linear Temporal Logic (LTL) and Computation Tree Logic (CTL). The toolbox intends to leverage the NuSMV model checker. ...

The problem of Pagerank is a simple one to state: Given a collection of websites, how do we rank them? The primary way of formulating this utilizes a transition matrix which relates how web pages interact with each other. We investigate what the effect of a low rank approximation for the transition matrix has on the power method and an inner-outer iteration for solving the Pagerank problem.

...We are able to achieve a verification accuracy which is only marginally inferior to the best results of minutiae-based algorithms published in the open literature. Our system performs better than a state-of-the-art minutiae-based system when the performance requirement of the application system does not demand a very low false acceptance rate. Finally, we show that the matching performance can be improved by combining the decisions of the matchers based on complementary (minutiae-based and filter-based) fingerprint information. ...

RIPE (Regulatory network Inference from joint Perturbation and Expression data) is a novel three-step method that integrates both perturbation data and steady state gene expression data in order to estimate a regulatory network. The ripe package is written in R, with additional functionality provided by a MATLAB executable file. The executable file uses a runtime engine called the MATLAB Compiler Runtime (MCR). The executable for different architectures is distributed on this site together with the R package itself.

...It performs approximate Bayesian computation for stochastic models having latent dynamics defined by stochastic differential equations (SDEs) and not limited to the "state-space" modelling framework. Both one- and multi-dimensional SDE systems are supported and partially observed systems are easily accommodated. Variance components for the "measurement error" affecting the data/observations can be estimated. A 50-pages Reference Manual is provided with two case-studies implemented and discussed. The methodology is based on the research article available at http://arxiv.org/abs/1204.5459 Author's research page is http://www.maths.lth.se/matstat/staff/umberto/

A MATLAB toolbox for time series analysis using state space models. Supports fully interactive model construction with MATLAB objects and efficient Kalman filter backend implemented in c.

...A note of caution: SDE Toolbox is no more developed but it's still downloadable. Its inferential capabilities can be considered surpassed (at best). Actually the parameter estimation methods were already far from the state-of-art when the project began in 2007 (!). The considered implemented parametric and non-parametric Monte Carlo likelihood methods were chosen for their ability to treat both one-dimensional and multivariate SDE systems, although the quality of the inferential results can't match those obtained using more advanced techniques. Nevertheless the toolbox capabilities to simulate numerical solutions of SDE systems are still valid and can serve as a useful starting point to those willing to simulate stochastic dynamical models easily.