• Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Model-based software prototyping enables the effective construction of design tools for new system design approaches in a very short time. In this paper, we show that explicit interface modelling is well-suited to integrate such prototyped tools into design environments. In addition, we point out how our model-based generative approach supports the evolution of prototypes very well. We present the prototyping methodology of Dual Dynamics Designer - a novel development tool for behaviour-oriented robot software. We demonstrate how a first prototype evolved into a fully-fledged design tool working as an integrated part in our robot design environment
    Rapid System Prototyping, 2000. RSP 2000. Proceedings. 11th International Workshop on; 02/2000
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: A widely used class of models for stochastic systems is hidden Markov models. Systems that can be modeled by hidden Markov models are a proper subclass of linearly dependent processes, a class of stochastic systems known from mathematical investigations carried out over the past four decades. This article provides a novel, simple characterization of linearly dependent processes, called observable operator models. The mathematical properties of observable operator models lead to a constructive learning algorithm for the identification of linearly dependent processes. The core of the algorithm has a time complexity of O(N + nm3), where N is the size of training data, n is the number of distinguishable outcomes of observations, and m is model state-space dimension.
    Neural Computation 07/2000; 12(6):1371-98. · 1.76 Impact Factor