10.18453/rosdok_id00005823 Strauß, Tobias Tobias Strauß http://d-nb.info/gnd/1136294554 https://orcid.org/0000-0002-5344-4188 Wustlich, Welf Welf Wustlich Labahn, Roger Roger Labahn http://d-nb.info/gnd/170999645 https://orcid.org/0000-0003-1901-9644 University of Rostock, Institute of Mathematics 2012 510 Mathematics 2012 en https://purl.uni-rostock.de/rosdok/id00005823 urn:nbn:de:gbv:28-rosdok_id00005823-5 This article develops approaches to generate dynamical reservoirs of ESNs with desired properties reducing the amount of randomness. It is possible to create weight matrices with a predefined singular value spectrum. The procedure guarantees stability (Echo State property) and minimizes the Impact of noise on the training process. The final reservoir types were already known in the literature but related Input weights were out of the scope of previous articles. But our experiments show, that well chosen input weights can improve performance.