of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy BLIND SEPARATION OF CONVOLUTIVE MIXTURES USING RENYI’S DIVERGENCE By Kenneth E. Hild II December 2003 Chair: Jose C. Principe Major Department: Electrical and Computer Engineering A new information-theoretic (IT) criterion is introduced,...

MOTIVATION Protein-protein interaction (PPI) plays an important role in understanding gene functions, and many computational PPI prediction methods have been proposed in recent years. Despite the extensive efforts, PPI prediction still has much room to improve. Sequence-based co-evolution methods include the substitution rate method and the mirror tree method, which compare sequence substitutio...

Numerous types of linear and nonlinear features have been extracted from the electrohysterogram (EHG) in order to classify labor and pregnancy contractions. As a result, the number of available features is now very large. The goal of this study is to reduce the number of features by selecting only the relevant ones which are useful for solving the classification problem. This paper presents thr...

This project explores methods for carrying out projections arising in the information geometry of the exponential family of probability models. Kullback-Leibler divergence serves as the distance measure between probability models in this context. The applications include maximum likelihood parameter estimation given sample paths of an unknown density as well as model reduction where one wishes ...

Introduction: The incidence of breast cancer increases with the rate of 1-2% at the world. Radiation therapy is one of the available choices for breast cancer treatment. The single isocentre half-beam block technique is considered as a standard technique to avoid hot and cold spots within the PTV. The major advantage of half beam technique is that the both contralateral breast...

Restricted Boltzmann Machines (RBMs) and Deep Belief Networks have been demonstrated to perform efficiently in a variety of applications, such as dimensionality reduction, feature learning, and classification. Their implementation on neuromorphic hardware platforms emulating large-scale networks of spiking neurons can have significant advantages from the perspectives of scalability, power dissi...

In this paper, we introduce a goodness of fit test for expo- nentiality based on Lin-Wong divergence measure. In order to estimate the divergence, we use a method similar to Vasicek’s method for estimat- ing the Shannon entropy. The critical values and the powers of the test are computed by Monte Carlo simulation. It is shown that the proposed test are competitive with other tests of exponentia...

compressible gas flow inside a convergent-divergent nozzle and its exhaust plume atdifferent nozzle pressure ratios (npr) have been numerically studied with severalturbulence models. the numerical results reveal that, the sst k–ω model give the bestresults compared with other models in time and accuracy. the effect of changes in value ofdivergence half-angle (ε ) on the nozzle performance, thru...