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Absfract-We propose, implement, and evaluate a class of nonstationary-state hidden Markov models (HMM's) having each state associated with a distinct polynomial regression function of time plus white Gaussian noise. The model represents the transitional acoustic trajectories of speech in a parametric manner, and includes the standard stationary-state HMM as(More)
Categorical data arise quite often in industrial experiments because of an expensive or inadequate measurement system for obtaining continuous data. When the failure probability/defect rate is small, experiments with categorical data provide little information regarding the effect of factors of interests and are generally not useful for product/process(More)
Standard practice in analyzing data from different types of experiments is to treat data from each type separately. By borrowing strength across multiple sources, an integrated analysis can produce better results. Careful adjustments need to be made to incorporate the systematic differences among various experiments. To this end, some Bayesian hierarchical(More)
Modeling experiments with qualitative and quantitative factors is an important issue in computer modeling. A framework for building Gaussian process models that incorporate both types of factors is proposed. The key to the development of these new models is an approach for constructing correlation functions with qualitative and quantitative factors. An(More)
To search for an optimum in a large search space, Wu, Mao, Ma (1990) suggested the SEL-method to find an optimal setting. Genetic algorithms (GAs) can be used to improve upon this method. To make the search procedure more efficient, new ideas of forbidden array and weighted mutation are introduced. Relaxing the condition of orthogonality, GAs are able to(More)