chaotic_init

chaotic_init([rng], [T], dims...;
    extra_edge_probability=T(0.1), spectral_radius=one(T),
    return_sparse=false)

Construct a chaotic reservoir matrix using a digital chaotic system (Xie et al., 2024).

The matrix topology is derived from a strongly connected adjacency matrix based on a digital chaotic system operating at finite precision. If the requested matrix order does not exactly match a valid order the closest valid order is used.

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

• extra_edge_probability: Probability of adding extra random edges in the adjacency matrix to enhance connectivity. Default is 0.1.
• desired_spectral_radius: The target spectral radius for the reservoir matrix. Default is one.
• return_sparse: If true, the function returns the reservoir matrix as a sparse matrix. Default is false.

Examples

julia> res_matrix = chaotic_init(8, 8)
┌ Warning: 
│ 
│     Adjusting reservoir matrix order:
│         from 8 (requested) to 4
│     based on computed bit precision = 1. 
│ 
└ @ ReservoirComputing ~/.julia/dev/ReservoirComputing/src/esn/esn_inits.jl:805
4×4 SparseArrays.SparseMatrixCSC{Float32, Int64} with 6 stored entries:
   ⋅        -0.600945   ⋅          ⋅ 
   ⋅          ⋅        0.132667   2.21354
   ⋅        -2.60383    ⋅        -2.90391
 -0.578156    ⋅         ⋅          ⋅