From the diffusion equation
$$ \frac{dx_i^K}{dt} = D_K \sum_{j=1}^{N} w_{ij}^K (x_j^K - x_i^K) + \sum_{L=1}^{M} D_{KL}(x_i^L - x_i^K), $$
$$ \mathcal{L} = \left( \begin{array}{c|c} D_1 L_1 + D_x I & -D_x I \\\hline -D_x I & D_2 L_2 + D_x I \end{array} \right)$$
where \( L_i \) is the Laplacian of layer \(i\), \(D_i\) is the diffusion coefficient of the layer.
Incoming Links #
Related Articles (Article 0) #
Suggested Pages #
- 0.528 Caenorhabditis elegans
- 0.233 C. elegans
- 0.025 Laplacian
- 0.013 Adjacency matrix
- 0.013 Fan Chung
- 0.013 Eigenvalues and eigenvectors
- 0.010 Network science
- 0.007 Network datasets
- 0.006 Spectral graph theory
- 0.003 Innovation
- More suggestions...