This paper describes a generalization of previous meth­ ods for constructing tree-structured belief network with hidden variables. The major new feature of the de­ scribed method is the ability to produce a tree decom­ position even when there are errors in the correlation data among the input variables. This is an important extension of existing methods since the correlational co­ efficients u...

The new Apexum procedure (Apexum Ltd, Or-Yehuda, Israel) is based on a minimally invasive removal of periapical chronically inflamed tissues through a root canal access. Apexum procedure (a novel method that allows for the removal or debulking of periapical tissues without using scalpels, periosteal elevators, or sutures) results in significant less postoperative discomfort or pain than convent...

The decoding capabilities of algebraic algorithms, mainly the Berlekamp-Massey algorithm, the Euclidean algorithm and our generalizations of these algorithms, are basically constrained by the minimum distance bounds of the codes. Thus, when the actual minimum distance of the codes is greater than that given by the bounds, these algorithms usually cannot fully utilize the error-correcting capabi...

We recently discovered novel discriminative training criteria following a principled approach. In this approach training criteria are developed from error bounds on the global error for pattern classification tasks that depend on non-trivial loss functions. Automatic speech recognition (ASR) is a prominent example for such a task depending on the non-trivial Levenshtein loss. In this context, t...

Various criteria are proposed to select the number of hidden neurons in artificial neural network (ANN) models and based on the criterion evolved an intelligent ensemble neural network model is proposed to predict wind speed in renewable energy applications. The intelligent ensemble neural model based wind speed forecasting is designed by averaging the forecasted values from multiple neural net...

We report on a simplified representation of Multi-Input Multi-Output (MIMO) systems and propose a Minimum Bit Error Rate (MBER) diagonal precoder. Assuming that channel information can be available at the transmitter, we show that the proposed representation decouples the MIMO channel into parallel subchannels, which greatly facilitates and speeds up further processing. Using traditional criter...

The NP multiple criteria minimum spanning tree as several applications into the network design problems. In this paper, we first introduce some properties than can help to characterize the problem, as well as to produce heuristics to solve it in a more efficient way. In the second part, we propose an application of the Multiple Objective Network optimization based on the Ant Colony Optimization...

This paper derives two new information theoretic linear regression criteria based on the minimum message length principle. Both criteria are invariant to full rank affine transformations of the design matrix and yield estimates that are minimax with respect to squared error loss. The new criteria are compared against state of the art information theoretic model selection criteria on both real a...

We present an efficient discriminative training procedure utilizing phone lattices. Different approaches to expediting lattice generation, statistics collection, and convergence were studied. We also propose a new discriminative training criterion, namely, minimum phone frame error (MPFE). When combined with the maximum mutual information (MMI) criterion using I-smoothing, replacing the standar...