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Found 5 papers, 1 papers with code
Time-Graph Frequency Representation with Singular Value Decomposition for Neural Speech Enhancement
However, most methods suffer from the alignment modeling of amplitude and phase (real and imaginary pairs) in a two-stream network framework, which inevitably incurs performance restrictions.
The Graph feature fusion technique for speaker recognition based on wav2vec2.0 framework
The GNN takes all the output features as the graph signal data and extracts the related graph structure information of features for speaker recognition.
Universal Graph Filter Design based on Butterworth, Chebyshev and Elliptic Functions
In this paper, we propose to design universal IIR graph filters with low computational complexity by using three kinds of functions, which are Butterworth, Chebyshev, and Elliptic functions, respectively.
Weighted Mean and Median graph Filters with Attenuation Factor for Sensor Network
This paper proposes a weighted attenuation k-hop graph, which depicts the spatial neighbor nodes with their hops from the central node.
Optimal Fractional Fourier Filtering in Time-vertex Graphs signal processing
Furthermore, the optimal time-vertex graph filter in fractional domains is also developed, using the graph fractional Laplacian operator and graph fractional Fourier transform.
