… Furthermore, the deep learningbased approach is more robust than conventional methods
… In summary, deep learning is a promising tool for channel estimation and signal detection in …

… to identify the signal modulation. Therefore, during the signal detection procession, we
identify them in the same format, and only detect the signal presence or absence. Through the …

… 90% classification accuracy when the signal is in a high SNR … a distributed sensor network
using deep learning models. A … , our deep learning model targets signal protocol detection in …

… deep learning method, which has demonstrated superior ability of functional fitting, we propose
to adopt a deep … , “Power of deep learning for channel estimation and signal detection in …

… of DL-SR methods on binary signal detection performance. … binary signal detection performance
of a suboptimal observer. … basic theory relating to binary signal detection tasks, NOs, and …

… a new signal detection scheme based on deep learning. To address the challenges of
signal detection, we propose the method which integrates the ensemble deep learning with the …

… CONCLUSION In this paper, the deep learning-based MIMO signal detection techniques
for conventional MIMO transmitters are proposed. The DNN based detection can achieve the …

… We propose a novel deep learning method called BN 3 for P300 signal detection. Our
method is fully data-driven while achieving the state-of-art character recognition performance by …

… the deep learning based receiver structure in [1]. In particular, the deep learning based MIMO
detector … ways such as the reinforcement learning [3], [4] and meta-learning method [5], [6]. …

… Our result that deep learning networks consistently outperformed other baselines, is … improved
performance over other supervised learning methods for acoustic signal classification [39]. …