Separation capacity of linear reservoirs with random connectivity matrix

arXiv:2404.17429v1 Announce Type: cross
Abstract: We argue that the success of reservoir computing lies within the separation capacity of the reservoirs and show that the expected separation capacity of random linear reservoirs is fully characterised by the spectral decomposition of an associated generalised matrix of moments. Of particular interest are reservoirs with Gaussian matrices that are either symmetric or whose entries are all independent. In the symmetric case, we prove that the separation capacity always deteriorates with time; while for …

abstract arxiv capacity computing connectivity cs.lg lies linear math.pr matrix moments random show stat.ml success type