In this paper, a novel spatial feature, namely maximum distance-gradient-magnitude (MDGM), is defined for registration tasks. For each voxel in an image, the MDGM feature encodes spatial information at a global level, including both edges and distances. We integrate the MDGM feature with intensity into a two-element attribute vector and adopt multi-dimensional mutual information as a similarity...

In this paper we study data from financial markets using an information-theory tool that we call the normalised Mutual Information Rate and show how to use it to infer the underlying network structure of interrelations in foreign currency exchange rates and stock indices of 14 countries world-wide and the European Union. We first present the mathematical method and discuss about its computation...

Mutual information (MI) is a widely used similarity metric for multimodality image registration. However, it involves an extremely high computational time especially when it is applied to volume images. Moreover, its robustness is affected by existence of local maxima. The multi-resolution pyramid approaches have been proposed to speed up the registration process and increase the accuracy of th...

In this work, we apply two concepts from network theory – network entropy and mutual information – to characterize the agility of network-form organizations. These concepts are developed from Shannon’s work on information entropy. We define the notions of network entropy and mutual information pertinent to measuring the structural evolution of organizations. We then show the application of netw...

In this work we show that entropy (H) and mutual information (MI) can be used as methods for extracting spatially localized features for classification purposes. In order to increase accuracy of entropy estimation, we use a Bayesian approach with a Dirichlet prior to derive estimation equations. We calculate the H and MI features for each electrode (H) and pair of electrodes (MI) in three frequ...

A spectrotemporal method based on Mutual Information (MI) is proposed for pitch estimation of voiced speech signals. We use MI as the similarity measure between voiced speech segments and their delayed version. Instead of measuring linear dependencies, MI measures statistical dependency, which suits the dynamic characteristic of speech signals. Besides, higher-order statistics are directly enco...

Quantifying the degree to which sex determination depends on the environment can yield insight into the evolution, ecological dynamics, and functional aspects of sex determination. In temperature-dependent sex determination (TSD), theory often predicts a complete dependence of sex on temperature, with a switch-like reaction norm. However, empirical data suggest more shallow relationships betwee...

Mutual Information (MI) estimation is an important component of several data mining tasks (e.g feature selection). In classi cation settings, MI estimation essentially depends on the estimation of the ratio of two probability densities. Using a recently developed method of density-ratio estimation, which is constructive in nature, new estimators for MI can be derived. In this paper we consider ...

In this paper, we analyze the semiblind mutual information (MI) between the input and output of a MIMO channel. To that end we consider the popular block fading model. We assume that some training/pilot symbols get inserted at the beginning of each burst. We show that the average MI over a transmission burst can be decomposed into symbol position dependent contributions. The MI component at a c...

Seizure and synchronization are related to each other in complex manner. Altered synchrony has been implicated in loss of consciousness during partial seizures. However, the mechanism of altered consciousness following termination of seizures has not been studied well. In this work we used bivariate mutual information as a measure of synchronization to understand the neural correlate of altered...