249 citations · 571 across the 42 of their papers we have counts for
50 papers
Neural Estimation and Optimization of Directed Information over Continuous Spaces
Dor Tsur, Ziv Aharoni, Ziv Goldfeld +1
This work develops a new method for estimating and optimizing the directed information rate between two jointly stationary and ergodic stochastic processes. Building upon recent ad…
A Study on MIMO Channel Estimation by 2D and 3D Convolutional Neural Networks
Ben Marinberg, Ariel Cohen, Eilam Ben-Dror +1
In this paper, we study the usage of Convolutional Neural Network (CNN) estimators for the task of Multiple-Input-Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-O…
Low PAPR waveform design for OFDM SYSTEM based on Convolutional Auto-Encoder
Yara Huleihel, Eilam Ben-Dror, Haim H. Permuter
This paper introduces the architecture of a convolutional autoencoder (CAE) for the task of peak-to-average power ratio (PAPR) reduction and waveform design, for orthogonal frequen…
Amended Cross Entropy Cost: Framework For Explicit Diversity Encouragement
Ron Shoham, Haim Permuter
Cross Entropy (CE) has an important role in machine learning and, in particular, in neural networks. It is commonly used in neural networks as the cost between the known distributi…
Capacity of Continuous Channels with Memory via Directed Information Neural Estimator
Ziv Aharoni, Dor Tsur, Ziv Goldfeld +1
Calculating the capacity (with or without feedback) of channels with memory and continuous alphabets is a challenging task. It requires optimizing the directed information (DI) rat…
Highway State Gating for Recurrent Highway Networks: improving information flow through time
Ron Shoham, Haim Permuter
Recurrent Neural Networks (RNNs) play a major role in the field of sequential learning, and have outperformed traditional algorithms on many benchmarks. Training deep RNNs still re…