Riemannian Gradient Descent for Joint Blind Super-Resolution and Demixing in ISAC
This research paper presents a novel Riemannian Gradient Descent (RGD) method for efficiently solving the Joint Blind Super-Resolution and Demixing (JBSD) problem in Integrated Sensing and Communication (ISAC) systems, offering theoretical guarantees of linear convergence and robustness to frequency separation conditions.
Subband Splitting: An Efficient Technique for Solving the Block Permutation Problem in Determined Blind Source Separation
The proposed subband splitting technique effectively solves the block permutation problem in determined blind source separation by splitting the entire frequency range into overlapping subbands and sequentially applying a blind source separation method to each subband.
Blind Source Separation of Single-Channel Mixtures via Multi-Encoder Autoencoders: A Comprehensive Analysis
Die vorgestellte Methode nutzt Multi-Encoder-Autoencoder für die Blind Source Separation ohne starke Anwendungsspezifische Voraussetzungen.
Single-Channel Mixtures Blind Source Separation via Multi-Encoder Autoencoders
提案された方法は、単一チャンネルの非線形混合物に対する盲目的なソース分離を可能にしました。
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