Add to ORKGIn this paper we present a first approach to the definition of different entropy measures for probabilistic P systems in order to obtain some quantitative parameters showing how complex the evolution of a P system is. To achieve this, we define two possible measures, the first one to reflect the entropy of the P system considered as the state space of possible computations, and the second one to reflect the change of the P system as it evolves.Ministerio de Ciencia y Tecnología TIC2002-04220-C03-0
Statistical complexity measures (SCM) are the composition of two ingredients: (i) entropies and (ii)...
<p>Algorithmic probability is traditionally defined by considering the output of a universal machine...
This thesis is a collection of essays on probability models for complex systems. Chapter 1 is an int...
In this paper we present a first approach to the definition of different entropy measures for proba...
Abstract: In this paper we present a first approach to the definition of different entropy measures ...
This paper is part of a series addressing the empirical/statistical distribution of the diversity of...
Given a probability space, we analyze the uncertainty, that is, the amount of information of a finit...
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-54072-6_22In...
A generalized Statistical Complexity Measure (SCM) is a functional that characterizes the probabilit...
We construct a complexity measure from first principles, as an average over the ‘‘obstruction agains...
The aim of the thesis is to define, develop, and consider applications of different measures of dyna...
Measuring the complexity of dynamical systems is important in order to classify them and better unde...
In this note we propose a method that permits to describe in a uniform man- ner variants of probabi...
We introduce dynamical probabilistic P systems, a variant where probabilities associated to the rule...
We study how statistical complexity depends on the system size and how the complexity of the whole s...
Statistical complexity measures (SCM) are the composition of two ingredients: (i) entropies and (ii)...
<p>Algorithmic probability is traditionally defined by considering the output of a universal machine...
This thesis is a collection of essays on probability models for complex systems. Chapter 1 is an int...
In this paper we present a first approach to the definition of different entropy measures for proba...
Abstract: In this paper we present a first approach to the definition of different entropy measures ...
This paper is part of a series addressing the empirical/statistical distribution of the diversity of...
Given a probability space, we analyze the uncertainty, that is, the amount of information of a finit...
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-54072-6_22In...
A generalized Statistical Complexity Measure (SCM) is a functional that characterizes the probabilit...
We construct a complexity measure from first principles, as an average over the ‘‘obstruction agains...
The aim of the thesis is to define, develop, and consider applications of different measures of dyna...
Measuring the complexity of dynamical systems is important in order to classify them and better unde...
In this note we propose a method that permits to describe in a uniform man- ner variants of probabi...
We introduce dynamical probabilistic P systems, a variant where probabilities associated to the rule...
We study how statistical complexity depends on the system size and how the complexity of the whole s...
Statistical complexity measures (SCM) are the composition of two ingredients: (i) entropies and (ii)...
<p>Algorithmic probability is traditionally defined by considering the output of a universal machine...
This thesis is a collection of essays on probability models for complex systems. Chapter 1 is an int...