Hidden Markov models (HMMs) are powerful statistical models that have found successful applications in Information Extraction (IE). In current approaches to applying HMMs to IE, a...
We propose a novel BIST technique for non-scan sequential circuits which does not modify the circuit under test. It uses a learning algorithm to build a hardware test sequence gen...
This paper concentrates on speech duration distributions that are usually invariant to noises and proposes a noise-robust and real-time voice activity detector (VAD) using the hid...
Xianglong Liu, Yuan Liang, Yihua Lou, He Li, Baoso...
Background: The Baum-Welch learning procedure for Hidden Markov Models (HMMs) provides a powerful tool for tailoring HMM topologies to data for use in knowledge discovery and clus...
The problem of discrete universal filtering, in which the components of a discrete signal emitted by an unknown source and corrupted by a known discrete memoryless channel (DMC) ar...