8 citations · 13 across the 5 of their papers we have counts for
7 papers
Parallel and Limited Data Voice Conversion Using Stochastic Variational Deep Kernel Learning
Mohamadreza Jafaryani, Hamid Sheikhzadeh, Vahid Pourahmadi
Typically, voice conversion is regarded as an engineering problem with limited training data. The reliance on massive amounts of data hinders the practical applicability of deep le…
Fast Classification with Sequential Feature Selection in Test Phase
Ali Mirzaei, Vahid Pourahmadi, Hamid Sheikhzadeh +1
This paper introduces a novel approach to active feature acquisition for classification, which is the task of sequentially selecting the most informative subset of features to achi…
Progressive Transmission using Recurrent Neural Networks
Mohammad Sadegh Safari, Vahid Pourahmadi, Patrick Mitran +1
In this paper, we investigate a new machine learning-based transmission strategy called progressive transmission or ProgTr. In ProgTr, there are b variables that should be transmit…
Pilot Pattern Design for Deep Learning-Based Channel Estimation in OFDM Systems
Mehran Soltani, Vahid Pourahmadi, Hamid Sheikhzadeh
In this paper, we present a downlink pilot design scheme for Deep Learning (DL) based channel estimation (ChannelNet) in orthogonal frequency-division multiplexing (OFDM) systems.…
Propagation Channel Modeling by Deep learning Techniques
Shirin Seyedsalehi, Vahid Pourahmadi, Hamid Sheikhzadeh +1
Channel, as the medium for the propagation of electromagnetic waves, is one of the most important parts of a communication system. Being aware of how the channel affects the propag…
Deep Feature Selection using a Teacher-Student Network
Ali Mirzaei, Vahid Pourahmadi, Mehran Soltani +1
High-dimensional data in many machine learning applications leads to computational and analytical complexities. Feature selection provides an effective way for solving these proble…
Deep Learning-Based Channel Estimation
Mehran Soltani, Vahid Pourahmadi, Ali Mirzaei +1
In this paper, we present a deep learning (DL) algorithm for channel estimation in communication systems. We consider the time-frequency response of a fast fading communication cha…