Machine learning algorithms are designed to capture complex relationships between
features. In this context, the high dimensionality of data often results in poor model …

Root cause analysis is an important step in process monitoring. In the related research field,
the popular causality analysis technique, transfer entropy (TE), has been adopted for its …

Many patients experience motor and sensory impairments after stroke, leading to gait
disturbances. Analysis of muscle modulation mode during walking can provide evidence for …

Novel approaches to estimate information measures using neural networks are well-
celebrated in recent years both in the information theory and machine learning communities …

The information relationship between real estate investment trusts and stock markets has
garnered significant interest in finance; however, the time-varying information flow between …

Objectives Comprehension of speech in adverse listening conditions is challenging for
hearing-impaired (HI) individuals. Noise reduction (NR) schemes in hearing aids (HAs) have …

We present novel data-processing inequalities relating the mutual information and the
directed information in systems with feedback. The internal deterministic blocks within such …

The foreign exchange (FX) market has evolved into a complex system where locally
generated information percolates through the dealer network via high-frequency …

Blast furnace ironmaking is a key process in iron and steel production, and the fuel ratio has
an important impact on the smelting efficiency, cost and environmental impact of the blast …

Transfer entropy can to a certain degree assess the direction in addition to the strength of
the couplings within dynamic time series. The greater the transfer entropy, the greater the …