Estimation of distribution algorithm (EDA) can solve more complicated problems than its predecessor (Genetic Algorithm). EDA uses various methods to probabilistically model a group of highly fit individuals. Calculating the model in sophisticated EDA is very time consuming. To reduce the model building time, the authors propose compressed chromosome encoding. A chromosome is encoded using a for...

Hidden Markov Models are commonly trained using algorithms derived from gradient-based methods such as the Baum-Welch procedure. We describe a new representation of discrete observation HMMs that permits them to be trained using Population-Based Incremental Learning (PBIL), a variant of genetic learning that combines evolutionary optimization and hill-climbing Baluja and Caruana, 1995]. In this...

introduction: solubility of mineral trioxide aggregate (mta) is an important characteristic that affects other properties such as microleakage and biocompatibility. distilled water (dw) has previously been used for solubility tests. this experimental study compared the solubility of mta in dw, synthetic tissue fluid (stf) and new simulated plasma (sp). methods and materials: in this study, 36 s...

Seven test statistics known to be robust to the combined effects of nonnormality and variance heterogeneity were compared for their sensitivity to detect treatment effects in a one-way completely randomized design containing four groups. The six Welch-James-type heteroscedastic tests adopted either symmetric or asymmetric trimmed means, were transformed for skewness, and used a bootstrap method...

Hidden Markov models have been used to restore recorded signals of single ion channels buried in background noise. Parameter estimation and signal restoration are usually carried out through likelihood maximization by using variants of the Baum-Welch forward-backward procedures. This paper presents an alternative approach for dealing with this inferential task. The inferences are made by using ...

In 1889 when I began the study of medicine, many medical students still had preceptors. I was fortunate to have as my "guide, philosopher and friend," Dr. Charles Pemberton Murray, a graduate of Princeton and of the College of Physicians and Surgeons in New York. When he heard that I was to study medicine, he suggested that I ride over to his house, a couple of miles east of Sierra Madre where ...

In this paper, we propose a filterbank-based technique to extract more robust and discriminative features for the application of telephony speech recognition. First, we propose an extended Lerner grouping method to approximate the shape of the Mel filters in MFCC while reducing the cross-correlation between filterbank outputs. Then we used welch processing to reduce the variance of the spectral...

This paper presents a new method of feature dimension reduction in hidden Markov modeling (HMM) for speech recognition. The key idea is to apply reduced rank maximum likelihood estimation in the M-step of the usual Baum-Welch algorithm for estimating HMM parameters such that the estimates of the Gaussian distribution parameters are restricted in a sub-space of reduced dimensionality. There are ...

The Welch (1939) uniform distribution example,  v U(−2  +12) ∈R, ever since its introduction, continues to be used as one of few crucial examples in debates concerning the problems of initial vs. final precision and conditional vs. unconditional inference. The primary aim of this paper is, first, to argue that none of the proposed inference procedure gives rise to satisfactory results in ...

Hidden Markov modeling (HMM) techniques have been applied in the past few years to characterize single ion channel current events at low signal-to-noise ratios (SNR’s). In this paper, an adaptation of the forward-backward procedure and Baum–Welch algorithm is presented to model ion channel kinetics under conditions of correlated and state-dependent excess noise like that observed in patch-clamp...