[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
[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.
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