Correlated information between multiple views can provide useful information for building robust classifiers. One way to extract correlated features from different views is using canonical correlation analysis (CCA). However, CCA is an unsupervised method and can not preserve discriminant information in feature extraction. In this paper, we first incorporate discriminant information into CCA by...

In this paper, two new methods, Temporal evolution of Detrended Cross-Correlation Analysis (TDCCA) and Temporal evolution of Detrended Partial-Cross-Correlation Analysis (TDPCCA), are proposed by generalizing DCCA and DPCCA. Applying TDCCA/TDPCCA, it is possible to study correlations on multi-time scales and over different periods. To illustrate their properties, we used two climatological exam...

In this paper, we analyze empirical data, accounting for coordination processes between complex systems (bimanual coordination, interpersonal coordination, and synchronization with a fractal metronome), by using a recently proposed method: detrended cross-correlation analysis (DCCA). This work is motivated by the strong anticipation hypothesis, which supposes that coordination between complex s...

In this paper, we investigate cross-correlations between crude oil and agricultural commodity markets. Based on a popular statistical test proposed by Podobnik et al. (2009), we find that the linear return cross-correlations are significant at larger lag lengths and the volatility cross-correlations are highly significant at all of the lag lengths under consideration. Using a detrended cross-co...

The use of biomass as an energy source has advanced in recent decades, given the scientific evidence that it is a solution to environmental problems faced globally. In this context, biofuels derived from have prominent role. Among countries where alternative most promising, Brazil stands out, just behind USA. It is, therefore, necessary assess whether such replacement economically viable. For a...

Esterel Technologies’ SCADE Suite is one of the most important development tools for software for safety-critical systems. It is used for designing many critical components of aerospace, automotive and transportation applications. For such systems safety analysis is a key requirement in the development process. In this paper we show how one formal safety analysis method – Deductive Cause-Conseq...

A model performing mesh partitioning into computationally equivalent mesh parts on regular square lattices using a diffusion controlled cellular automaton (DCCA) is proposed and studied in this article. Every processor has assigned a domain seed at the beginning of a simulation. Algorithm works with growth of seeds and migration of domain borders, the later is triggered when the difference of d...

An empirical test on long memory between price and trading volume of China metals futures market was given with MF-DCCA method. The empirical results show that long memory feature with a certain period exists in price−volume correlation and a further proof was given by analyzing the source of multifractal feature. The empirical results suggest that it is of important practical significance to b...

We examine Deep Canonically Correlated LSTMs as a way to learn nonlinear transformations of variable length sequences and embed them into a correlated, fixed dimensional space. We use LSTMs to transform multi-view time-series data non-linearly while learning temporal relationships within the data. We then perform correlation analysis on the outputs of these neural networks to find a correlated ...