In this paper, we explore the properties of holographic entanglement entropy (HEE), mutual information (MI) and purification (EoP) in Lifshitz theory. These informational quantities exhibit some universal dual field For most configuration parameters temperatures, these change monotonously with dynamical critical exponent $z$. However, also observe non-monotonic behaviors for specific spaces tem...

During the past decades, to study high-dimensional data in a large variety of problems, researchers have proposed many Feature Extraction algorithms. One of the most effective approaches for optimal feature extraction is based on mutual information (MI). However it is not always easy to get an accurate estimation for high dimensional MI. In terms of MI, the optimal feature extraction is creatin...

The mutual information concept is used to study the distribution of speech information in frequency and in time. The main focus is on the information that is relevant for phonetic classi cation. A large database of hand-labeled uent speech is used to (a) compute the mutual information (MI) between a phonetic classi cation variable and one spectral feature variable in the time-frequency plane an...

This paper presents a novel approach for efficient feature extraction using mutual information (MI). In terms of mutual information, the optimal feature extraction is creating a feature set from the data which jointly have the largest dependency on the target class. However, it is not always easy to get an accurate estimation for high-dimensional MI. In this paper, we propose an efficient metho...

Image registration is one of the fundamental tasks within image processing. It has wide applications in the fields of medical imaging, computer vision, statistical modeling etc. It is required when one wants to combine valuable statistical information from multiple images, possibly acquired using different modalities, at different time points or from different subjects, or to compare or integra...

Mutual information (MI) is a standard measure of statistical dependence of random variables. However, due to the log function and the ratio of probability densities included in MI, it is sensitive to outliers. On the other hand, the L2-distance variant of MI called quadratic MI (QMI) tends to be robust against outliers because QMI is just the integral of the squared difference between the joint...

− Information on physical image quality of medical images is important for imaging system assessment in order to promote and stimulate the development of stateof-the-art imaging systems. In this paper, we present a method for measuring physical performance of medical imaging systems. In this method, mutual information (MI) which is a concept from information theory was used to measure combined ...

In this paper we have presented an IntegratedWavelet Neural Network (WNN) model and Mutual Information (MI)-based input selection algorithm for time series prediction. Based on MI the proper input variables, which describe the time series’ dynamics properly, will be selected. The WNN Prediction model uses selected variables and predicts the future. This model utilized for time series prediction...