… consider the impulse noise. The main objective or research problem that this paper want to
address is deep learning based Polar code decoding in the memeory impulse noise channels…

… impulsive noise channels. • We show that the proposed deep neural network can be trained
on an impulsive noise … sphere decoder in the presence of Gaussian and impulsive noise, we …

… of a machine learning-based decoder over impulsive noise … called GatedNet for decoding
over impulsive noise channels, … impact of the impulsive noise to neural network decoders. The …

… Symbol Demapper and Iterative Decoding: The non-Gaussian nature of the impulsive noise
… decoder for error correction. As a more advanced approach, the process of impulsive noise …

… proposed deep learning decoder with … Deep Learning neural network through supervised
learning which provide a new loss function is provided to counter the effects of impulsive noise. …

… machine learning system to adapt to AWGN, this project aims to experiment with a different
stochastic noise … specifically in an environment with impulsive noise where the system should …

… LSTM neural network decoder in [30]. This decoder adeptly addresses memory impulse
noise… Beyond harnessing the power of deep learning for targeted impulse noise attenuation, our …

… a deep learning approach to estimate the impulsive noise param… , incorporating impulsive
noise dynamics in the decoding … decoder (ie, the SCMA decoder) and an outer decoder (for the …

… demodulation and decoding blocks of the communication chain with neural networks was …
the traditional methods in the presence of impulse noise, with great reduction in computational …

… decoder can … decoder outputs spectral line-reconstruction results through FinalConv, as
shown in Figure 2c. Moreover, a reconstruction decoder is enabled when the detection decoder …