9 citations · 19 across the 5 of their papers we have counts for
5 papers
Simplified Minimal Gated Unit Variations for Recurrent Neural Networks
Joel Heck, Fathi M. Salem
Recurrent neural networks with various types of hidden units have been used to solve a diverse range of problems involving sequence data. Two of the most recent proposals, gated re…
Simplified Gating in Long Short-term Memory (LSTM) Recurrent Neural Networks
Yuzhen Lu, Fathi M. Salem
The standard LSTM recurrent neural networks while very powerful in long-range dependency sequence applications have highly complex structure and relatively large (adaptive) paramet…
A Basic Recurrent Neural Network Model
Fathi M. Salem
We present a model of a basic recurrent neural network (or bRNN) that includes a separate linear term with a slightly "stable" fixed matrix to guarantee bounded solutions and fast…
A RobustICA Based Algorithm for Blind Separation of Convolutive Mixtures
Zaid Albataineh, Fathi M. Salem
We propose a frequency domain method based on robust independent component analysis (RICA) to address the multichannel Blind Source Separation (BSS) problem of convolutive speech m…
Convex Cauchy Schwarz Independent Component Analysis for Blind Source Separation
Zaid Albataineh, Fathi M. Salem
We present a new high performance Convex Cauchy Schwarz Divergence (CCS DIV) measure for Independent Component Analysis (ICA) and Blind Source Separation (BSS). The CCS DIV measure…