Effective Training Principles of Physical Reservoirs
Researchers have developed new training principles for physical reservoir computers, focusing on optical phenomena. The study introduces methods like output pruning and regularization to combat overfitting and improve computational efficiency. Techniques such as variance filtering, branch and bound, and statistical filtering were compared against random pruning, with a focus on optimizing reservoir output sampling for improved performance, particularly in nonlinear tasks. AI