A hierarchical framework is proposed to address the issues of modeling different type of words in keyword spotting (KWS). Keyword models are built at various levels according to the availability of training set resources for each individual word. The proposed approach improves the performance of KWS even when no training speech is available for the keywords. It also suggests an easier way to co...

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In this paper, the issue of pth moment stability of a class of stochastic neural networks with mixed delays is investigated. By establishing two integro-differential inequalities, some new sufficient conditions ensuring pth moment exponential stability are obtained. Compared with some previous publications, our results generalize some earlier works reported in the literature, and remove some st...

We provide a new sequential predictors approach for the exponential stabilization of linear time-varying systems. Our method circumvents the problem of constructing and estimating distributed terms in the control laws, and allows arbitrarily large input delay bounds, pointwise time-varying input delays, and uncertainties. Instead of using distributed terms, our approach to handling longer delay...

Available solutions to sampled-data H 2 optimal control problems for systems with input delays begin with a conversion to a discrete-time problem with input delays, followed by a matching optimization method geared to handle delays. We propose to reverse that order and address the delay first, by an analog loop transformation. Hence, discretization and optimization involve no delays and are ame...

This paper studies the consensus problem for multi-agent systems with diverse input and communication delays. Decentralized consensus conditions are obtained based on the frequency-domain analysis and matrix theory. By these conditions, to achieve consensus under large input delays, one should use small interconnection gains or have small numbers of neighbors when the graph is kept connected. F...