Unsupervised learning methods often involve summarizing the data using a small number of parameters. In certain domains, only a small subset of the available data is relevant for ...
This paper describes a way of designing modulation filter by datadriven analysis which improves the performance of automatic speech recognition systems that operate in real envir...
In this paper, a variance constrained filtering problem is considered for systems with both non-Gaussian noises and polytopic uncertainty. A novel filter is developed to estimate t...
—In this paper, we show that minimizing the product of path lengths results in minimizing the probability of connection failure between a source and destination given two links h...
In this paper, an integrated resolution up-conversion and compression artifacts removal algorithm is proposed. Local image patterns are classified into object details or coding ar...