Speech recognition is conversion of human speech in to the text or control signal by the
means of intelligent algorithms. Speech recognition plays vital role in many biometric …

Abstract Blind Source Separation (BSS) is a task of separating a set of source signals from
mixed signal without (or very little information) of both the sources and the mixing process …

Fast independent component analysis (FastICA) algorithm separates the independent
sources from their mixtures by measuring non-Gaussian. FastICA is a common offline …

In this paper, we present a multiple concurrent occupant identification approach through
footstep-induced floor vibration sensing. Identification of human occupants is useful in a …

Given the large amount of data collected from social media, it is very difficult for users to
identify social events and understand their societies. In this paper, we propose a novel …

We present a new stochastic learning machine for speech separation based on the
variational recurrent neural network (VRNN). This VRNN is constructed from the …

Independent component analysis (ICA) is vital for unsupervised learning and blind source
separation (BSS). The ICA unsupervised learning procedure attempts to demix the …

Independent component analysis (ICA) is a popular approach for blind source separation
where the mixing process is assumed to be unchanged with a fixed set of stationary source …

One of the most commonly reported disabilities is vision loss, which can be diagnosed by an
ophthalmologist in order to determine the visual system of a patient. This procedure …

Deep Attractor Network (DANet) is the state-of-the-art technique in speech separation field,
which uses Bidirectional Long Short-Term Memory (BLSTM), but the complexity of the …