truedoublecycle

true_double_cycle([rng], [T], dims...; 
    cycle_weight=0.1, second_cycle_weight=0.1,
    return_sparse=false)

Creates a true double cycle reservoir, ispired by (Fu et al., 2023), with cycles built on the definition by (Rodan and Tino, 2011).

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

• cycle_weight: Weight of the upper cycle connections in the reservoir matrix. Default is 0.1.

• second_cycle_weight: Weight of the lower cycle connections in the reservoir matrix. Default is 0.1.

• return_sparse: flag for returning a sparse matrix. Default is false.

• cycle_kwargs, and second_cycle_kwargs: named tuples that control the kwargs for the weights generation. The kwargs are as follows:

  • sampling_type: Sampling that decides the distribution of weight negative numbers. If set to :no_sample the sign is unchanged. If set to :bernoulli_sample! then each weight can be positive with a probability set by positive_prob. If set to :irrational_sample! the weight is negative if the decimal number of the irrational number chosen is odd. If set to :regular_sample!, each weight will be assigned a negative sign after the chosen strides. strides can be a single number or an array. Default is :no_sample.
  • positive_prob: probability of the weight being positive when sampling_type is set to :bernoulli_sample!. Default is 0.5.
  • irrational: Irrational number whose decimals decide the sign of weight. Default is pi.
  • start: Which place after the decimal point the counting starts for the irrational sign counting. Default is 1.
  • strides: number of strides for assigning negative value to a weight. It can be an integer or an array. Default is 2.

Examples

julia> true_double_cycle(5, 5; cycle_weight = 0.1, second_cycle_weight = 0.3)
5×5 Matrix{Float32}:
 0.0  0.3  0.0  0.0  0.1
 0.1  0.0  0.3  0.0  0.0
 0.0  0.1  0.0  0.3  0.0
 0.0  0.0  0.1  0.0  0.3
 0.3  0.0  0.0  0.1  0.0