# Why does $I_N + D^{-\frac{1}{2}}AD^{-\frac{1}{2}}$ have eigenvalues in the range [0, 2]

In Semi-supervised classification with Graph Convolutional Networks, I am unable to understand few things.

Given an undirected graph having adjacency matrix $$A$$, degree matrix $$D_{ii} = \sum_j A_{ij}$$
normalized graph laplacian $$L = I_N + D^{-\frac{1}{2}}AD^{-\frac{1}{2}} = U \Lambda U^T$$, where $$\lambda_{max} \approx 2$$ (see page 3, 2nd paragraph, not sure which matrix they are talking about)
Then, $$I_N + D^{-\frac{1}{2}}AD^{-\frac{1}{2}}$$ has eigenvalues in the range [0, 2]. How?