pseudo_svd

pseudo_svd([rng], [T], dims...; 
    max_value=1.0, sparsity=0.1, sorted=true, reverse_sort=false,
    return_sparse=false)

Returns an initializer to build a sparse reservoir matrix with the given sparsity by using a pseudo-SVD approach as described in (Yang et al., 2018).

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

• max_value: The maximum absolute value of elements in the matrix. Default is 1.0
• sparsity: The desired sparsity level of the reservoir matrix. Default is 0.1
• sorted: A boolean indicating whether to sort the singular values before creating the diagonal matrix. Default is true.
• reverse_sort: A boolean indicating whether to reverse the sorted singular values. Default is false.
• return_sparse: flag for returning a sparse matrix. Default is false.
• return_diag: flag for returning a Diagonal matrix. If both return_diag and return_sparse are set to true priority is given to return_diag. Default is false.

Examples

julia> res_matrix = pseudo_svd(5, 5)
5×5 Matrix{Float32}:
 0.306998  0.0       0.0       0.0       0.0
 0.0       0.325977  0.0       0.0       0.0
 0.0       0.0       0.549051  0.0       0.0
 0.0       0.0       0.0       0.726199  0.0
 0.0       0.0       0.0       0.0       1.0