Echo　state　network　(ESN)　is　a　kind　of　recurrent　neural　network　without　involving　gradient　problem.　However,　the　reservoir　of　ESN　often　contains　hundreds　of　neurons,　whose　corresponding　high-dimensional　state　matrix　may　result　in　ill-conditioned　solution　problem.　To　solve　it,　the　condition　number-based　evolving　ESN　(CNEESN)　is　proposed,　whose　sub-reservoir　is　generated　by　condition　number　analysis　and　differential　evolution　algorithm　(DE).　Firstly,　the　influence　of　condition　number　on　output　weight　matrix　is　analyzed.　Secondly,　the　randomly　generated　singular　values　are　optimized　by　condition　number　and　DE　based　optimize　strategy.　Finally,　simulation　result　on　a　benchmark　dataset　has　shown　the　superiority　of　the　proposed　CNEESN.　©　2022　IEEE.