low_connectivity

low_connectivity([rng], [T], dims...;
                 return_sparse = false, connected=false,
                 in_degree = 1, radius = 1.0, cut_cycle = false)

Construct an internal reservoir connectivity matrix with low connectivity.

This function creates a square reservoir matrix with the specified in-degree for each node (Griffith et al., 2019). When in_degree is 1, the function can enforce a fully connected cycle if connected is true; otherwise, it generates a random connectivity pattern.

Arguments

• rng: Random number generator. Default is Utils.default_rng() from WeightInitializers.
• T: Type of the elements in the reservoir matrix. Default is Float32.
• dims: Dimensions of the reservoir matrix.

Keyword Arguments

• return_sparse: If true, the function returns the reservoir matrix as a sparse matrix. Default is false.
• connected: For in_degree == 1, if true a connected cycle is enforced. Default is false.
• in_degree: The number of incoming connections per node. Must not exceed the number of nodes. Default is 1.
• radius: The desired spectral radius of the reservoir. Defaults to 1.0.
• cut_cycle: If true, removes one edge from the cycle to cut it. Default is false.