Linear representations of probabilistic transformations induced by context transitions
نویسنده
چکیده
By using straightforward frequency arguments we classify transformations of probabilities which can be generated by transition from one preparation procedure (context) to another. There are three classes of transformations corresponding to statistical deviations of different magnitudes: (a) trigonometric; (b) hyperbolic; (c) hypertrigonometric. Each class is characterized by a perturbation of the ‘classical probabilistic rule’: (a) cos θ, (b) cosh θ, (c) both cos θ and cosh θ. Trigonometric transformations correspond to context-transitions that induce statistical deviations of relatively small magnitudes (in classical physics negligibly small); hyperbolic relatively large magnitudes. We found that not only preparation procedures described by conventional quantum formalism can have trigonometric probabilistic behaviour. We propose generalizations of C-linear space probabilistic calculus to describe non quantum (trigonometric and hyperbolic) probabilistic transformations.
منابع مشابه
A Probabilistic Model of Learning Fields in Islamic Economics and Finance
In this paper an epistemological model of learning fields of probabilistic events is formalized. It is used to explain resource allocation governed by pervasive complementarities as the sign of unity of knowledge. Such an episteme is induced epistemologically into interacting, integrating and evolutionary variables representing the problem at hand. The end result is the formalization of a p...
متن کاملQuantum probabilities ’ as context depending probabilities . Andrei Khrennikov School of Mathematics and Systems Engineering University of Växjö , S - 35195 , Sweden
We study transformations of conventional ('classical') probabilities induced by context transitions. It is demonstrated that the transition from one complex of conditions to another induces a perturbation of the classical rule for the addition of probabilistic alternatives. We classify such perturbations. It is shown that there are two classes of perturbations: (a) trigonometric interference; (...
متن کاملNormal Factor Graphs as Probabilistic Models
We present a new probabilistic modelling framework based on the recent notion of normal factor graph (NFG). We show that the proposed NFG models and their transformations unify some existing models such as factor graphs, convolutional factor graphs, and cumulative distribution networks. The two subclasses of the NFG models, namely the constrained and generative models, exhibit a duality in thei...
متن کاملOn the Efficiency of Deciding Probabilistic Automata Weak Bisimulation
Weak probabilistic bisimulation on probabilistic automata can be decided by an algorithm that needs to check a polynomial number of linear programming problems encoding weak transitions. It is hence polynomial, but not guaranteed to be strongly polynomial. In this paper we show that for polynomial rational probabilistic automata strong polynomial complexity can be ensured. We further discuss co...
متن کاملEmbedding Word Tokens using a Linear Dynamical System
Low dimensional representations of words allow accurate models to be trained on limited annotated data. While most word representations are context-independent, a natural way to induce representations for words in their particular context is to perform inference over latent variables in a probabilistic model. Given the recent success of continuous vector-space word representations, we provide s...
متن کامل