In this paper, we extend the Maximum Likelihood (ML) training algorithm to the Minimum classificnrtion Emor (MCE) training algorithm for optimal estimation of the state-dependent polynomial coefficients in the trended HMM [2]. The problem of automatic speech recognition is viewed as a discriminative dynamic data-fitting problem, where nlotiue (not absolute) closeness in fitting an array of dyna...

A statistical analysis of texture on the COBE-DMR rst year sky maps based on the genus and spot number is presented. A generalized 2 statistic is de ned in terms of \observable" quantities: the genus and spot density that would be measured by di erent cosmic observers. This strategy together with the use of Monte Carlo simulations of the temperature uctuations, including all the relevant experi...

We test a theory presented previously to account for the turbulent transport of magnetic uctuation energy in the solar wind and the related dissipation and heating of the ambient ion population. This theory accounts for the injection of magnetic energy through the damping of large-scale ow gradients such as wind shear and compression, and incorporates the injection of magnetic energy due to wav...

in today’s world renewable energy is highly demanding because of increasing oil and fuelprices, desire and necessity to avert irreversible climate damage and also the unreliability of the non -renewablesources. in renewable energy, water is an important source. previously water is used only for survivalof human being as much as food but no attentionhas been givenen to economical use and conserv...

This paper presents the theoretical development of new threshold autoregressive models based on trended time series. The theoretical arguments underlying the models are outlined and a nonlinear economic model is used to derive the speci cation of the empirical econometric models. Estimation and testing issues are considered and analysed. Additionally we apply the models to the empirical investi...

This technical appendix is a companion of main article. In Section 2 we show how to rewrite the Bellman equations in steady state in terms of de-trended variables. In Section 3 we detail the computational algorithm to solve for the policy functions of the problem faced by employed and unemployed workers, for given equilibrium quantities. Then, in subsections 3.2 and 3.1 we discuss how we solve ...

Most synapses form on small, specialized postsynaptic structures known as dendritic spines. The in ̄ux of Ca ions into such spinesÐthrough synaptic receptors and voltage-sensitive Ca channels (VSCCs)Ðtriggers diverse processes that underlie synaptic plasticity. Using two-photon laser scanning microscopy, we imaged action-potential-induced transient changes in Ca concentration in spines and dendr...

An overview of a statistical paradigm for speech recognition is given where phonetic and phonological knowledge sources, drawn from the current understanding of the global characteristics of human speech communication, are seamlessly integrated into the structure of a stochastic model of speech. A consistent statistical formalism is presented in which the submodels for the discrete, feature-bas...

In this paper, we report our recent work on applications of the MAP approach to estimating the time-varying polynomial Gaussian mean functions in the nonstationary-state or trended HMM. Assuming uncorrelatedness among the polynomial coefficients in the trended HMM, we have obtained analytical results for the MAP estimates of the time-varying mean and precision parameters. We have implemented a ...