In this paper, a novel binary phase shift keying demodulator based on 1-D convolutional
neural network (1-D CNN) is proposed. The utilization of neural networks to detect the …

In this paper, we propose a field programmable gate array (FPGA) implementation of a one-
dimensional convolution neural network (1D-CNN) demodulator for binary phase shift …

In wireless communication, signal demodulation under non-ideal conditions is one of the
important research topic. In this paper, a novel non-coherent binary phase shift keying …

In this paper we presented a neural network-based method to demodulate digital signals.
After training with different modulation schemes, the learning-based receiver can perform …

Demodulation techniques are of central importance for achieving intelligent receiving.
Improvement in demodulation performance enhances the overall performance of a …

In this paper an artificial neural network demodulator to demodulate binary frequency shift
keying signal is proposed. This demodulator has some important features compared with …

In recent years, deep learning is becoming more and more popular. It has been widely
applied to fields including image recognition, automatic speech recognition and natural …

In this paper the effect of training neural network BFSK demodulator with noisy data (sent by
transmitter and affected by channel) is discussed and the results is compared with …

Automatic modulation classification (AMC) aims to identify the modulation format of the
received signals corrupted by the noise, which plays a major role in radio monitoring. In this …

In this paper we present the symbol and bit error rate performance of the weak signal digital
communications system. We investigate orthogonal multiple frequency shift keying …