Theoretical and Applied Informatics

We present a novel quantum algorithm for the classification of images. The algorithm is constructed using principal component analysis and von Neuman quantum measurements. In order to apply the algorithm we present a new quantum representation of grayscale images.

In this paper we present the analysis of the gas usage for different types of buildings. First, we introduce the classical theory of building heating. This allows the establishment of theoretical relations between gas consumption time series and the outside air temperature for different types of buildings, residential and industrial. These relations imply dierent auto-correlations of gas usage time series as well as different cross-correlations between gas consumption and temperature time series for different types of buildings. Therefore, the autocorrelation and the cross-correlation were used to classify the buildings into three classes: housing, housing with high thermal capacity, and industry. The Hurst exponent was calculated using the global DFA to investigate auto-correlation, while the Kendall's τ rank coeficient was calculated to investigate cross-correlation.

In the presented paper we discuss pure versions of pushdown automata that have no extra non-input symbols. More specifically, we study pure multi-pushdown automata, which have several pushdown lists. We restrict these automata by the total orders defined over their pushdowns or alphabets and determine the accepting power of the automata restricted in this way. Moreover, we explain the significance of the achieved results and relate them to some other results in the automata theory.