Fig. 3From: Motor data-regularized nonnegative matrix factorization for ego-noise suppressionPart of an undirected graph where motor data vectors \(\bar {\boldsymbol {\alpha }}_{\ell }\), \(\ell =1,\dots,L\) are the nodes of the graph. The weights of the edges are given by Eq. 6: the more similar two motor data vectors are, the larger the weight of the connecting edge isBack to article page