Table 2 Fixed parameters.
From: Novelty and imitation within the brain: a Darwinian neurodynamic approach to combinatorial problems
Number of neurons | \(n_{\mathrm{neuron}}\) | 1000 |
Number of readout neurons | \(n_{\mathrm{readout}}\) | 1 |
Connection probability of sparse \(\varvec{Q}\) matrix | p | 0.1 |
Chaocity parameter | g | 1.5 |
Timestep | dt | 0.1 |
Signal generation time | \(t_{\mathrm{signal}}\) | 300 |
Learning rate of FORCE algorithm | \(\alpha\) | 1 |
Training time | \(t_{\mathrm{train}}\) | 300 |
Evaluation time | \(t_{\mathrm{evaluation}}\) | 30 |
Number of sine and cosine coefficients of initial signal | \(n_{\mathrm{Fourier}}\) | 5 |
