Single-channel blind separation of co-frequency signals based on convolutional network
Authors:
- Xiaoqi HouXHXiaoqi Hou
- Yong GaoYGYong Gao
- 27 July 2022
- journal article
- research article
- Published by Elsevier in Digital Signal Processing
- Vol. 129
Abstract
No abstract availableKeywords
This publication has 9 references indexed in Scilit:
- A hierarchical receptive network oriented to target recognition in SAR imagesPattern Recognition, 2022
- A lightweight and efficient neural network for modulation recognitionDigital Signal Processing, 2022
- Deep cascading network architecture for robust automatic modulation classificationNeurocomputing, 2021
- Single Channel Blind Source Separation Under Deep Recurrent Neural NetworkWireless Personal Communications, 2020
- Bi-Decoder Augmented Network for Neural Machine TranslationNeurocomputing, 2020
- Conv-TasNet: Surpassing Ideal Time–Frequency Magnitude Masking for Speech SeparationIEEE/ACM Transactions on Audio, Speech, and Language Processing, 2019
- Squeeze-and-Excitation NetworksIEEE Transactions on Pattern Analysis and Machine Intelligence, 2019
- Performance measurement in blind audio source separationIEEE Transactions on Audio, Speech, and Language Processing, 2006
- Per-Survivor Processing: a general approach to MLSE in uncertain environmentsIEEE Transactions on Communications, 1995