In this report we formally obtain some results regarding likelihood ratios and mutual information for (conditional) Poisson processes with stochastic intensity functions. Our results for likelihood ratios are an extension of results obtained recently by Snyderl ' Z by a somewhat different approach (Snyder considers the case where the stochastic intensity function is Markovian while our results ...

In this paper, we present a new algorithm to register multimodal images using mutual information in a fully diffeomorphic framework. Our driving motivation is to define a one-to-one mapping in CT/MR 3D pulmonary images acquired from patients with empyema. Due to the large amount of respiratory motion and the presence of strong pathologies, preserving the invertibility of the deformations can be...

background: the time and frequency features of motor unit action potentials (muaps) extracted from electromyographic (emg) signal provide discriminative information for diagnosis and treatment of neuromuscular disorders. however, the results of conventional automatic diagnosis methods using muap features is not convincing yet. objective: the main goal in designing a muap characterization system...

In this paper we use mutual information to study the distribution in time and frequency of information relevant for phonetic classi cation. A large database of hand-labeled uent speech is used to (a) compute the mutual information between phoneme labels and a point of logarithmic energy in the time-frequency plane and (b) compute the joint mutual information between phoneme labels and two point...

Many approaches have been proposed to find correlations in binary data. Usually, these methods focus on pair-wise correlations. In biology applications, it is important to find correlations that involve more than just two features. Moreover, a set of strongly correlated features should be non-redundant in the sense that the correlation is strong only when all the interacting features are consid...

Informative gene selection can have important implications for the improvement of cancer diagnosis and the identification of new drug targets. Individual-gene-ranking methods ignore interactions between genes. Furthermore, popular pair-wise gene evaluation methods, e.g. TSP and TSG, are helpless for discovering pair-wise interactions. Several efforts to discover pair-wise synergy have been made...