We introduce a method to learn a hierarchy of successively more abstract representations of complex data based on optimizing an information-theoretic objective. Intuitively, the optimization searches for a set of latent factors that best explain the correlations in the data as measured by multivariate mutual information. The method is unsupervised, requires no model assumptions, and scales line...

An information-theoretic approach for detecting interactions and information transfer between two systems is extended to interactions between dynamical phenomena evolving on different time scales of a complex, multiscale process. The approach is demonstrated in the detection of an information transfer from larger to smaller time scales in a model multifractal process and applied in a study of c...

In recent years, the popularity of wireless inductive power transfer (WIPT) system for electric vehicle battery charging (EVBC) is always ever-increasing. In the WIPT inductively coupled coil structure is the heart of the system and the mutual inductance (MI) between the coupled coils is the key factor for effective power transfer. This paper presents the analysis of mutual inductance between t...

This paper analyzes a legendary Chinese horse race problem involving the King of Qi and General Tianji which took place more than 2000 years ago. In this problem each player owns three horses of different speed classes and must choose the sequence of horses to compete against each other. Depending on the payoffs received by the players as a result of the horse races, we analyze two groups of co...

Abstract Hyperspectral images (HSI) present a wealth of information. It is distinguished by its high dimensionality. served humanity in many fields. The quantity HSI information represents double-edged sword. As consequence, their dimensionality must be reduced. Nowadays, several methods are proposed to overcome duress. most useful and essential solution selection approaches hyperspectral bands...

Transfer entropy (TE) is a model-free approach based on information theory to capture causality between variables, which has been used for the modeling and monitoring of, and fault diagnosis in, complex industrial processes. It is able to detect the causality between variables without assuming any underlying model, but it is computationally burdensome. To overcome this limitation, a hybrid meth...

One of the main problems in DNA and protein sequence comparisons is to decide whether observed similarity of two sequences should be explained by their relatedness or by mere presence of some shared internal structure, e.g., shared internal tandem repeats. The standard methods that are based on statistics or classical information theory can be used to discover either internal structure or mutua...

This paper presents a low probability of interception (LPI) radar waveform design method with a fixed average power constraint based on information theory. The Kullback–Leibler divergence (KLD) between the intercept signal and background noise is presented as a practical metric to evaluate the performance of the adversary intercept receiver in this paper. Through combining it with the radar per...

MUTUAL INFORMATION BASED FEATURE SELECTION FOR ACOUSTIC AUTISM DIAGNOSIS Pervasive Developmental Disorders (PDD) are known to affect children’s social interactions and mental development. Prosodic and linguistic cues can be used to diagnose the disorders at early ages. Computational paralinguistics can be applied for tele-monitoring and/or educating the children with PDD. For better understandi...

The main difficulty concerning optimizing the mutual information (MI) in reconfigurable intelligent surface (RIS)-aided communication systems with discrete signaling is inability to formulate this optimization problem an analytically tractable manner. Therefore, we propose use cutoff rate (CR) as a more metric for MI and introduce two methods maximize CR, assuming perfect knowledge of channel s...