To　design　the　structure　of　echo　state　network　(ESN),　a　pruning　algorithm　for　modular　echo　state　network　(PMESN)　based　on　sensitivity　analysis　is　proposed　in　this　paper.　The　reservoir　of　PMESN　is　made　up　of　independent　sub-reservoir　modular　networks.　The　weight　matrices　of　sub-reservoir　modular　networks　are　obtained　by　the　singular　value　decomposition　(SVD),　and　the　reservoir　is　generated　by　the　block　diagonal　matrix　theory.　The　residual　error0s　sensitivities　to　the　sub-reservoir　modular　networks　are　deflned　by　their　outputs　and　weight　vectors　connecting　to　the　output　layer.　The　signiflcance　of　the　sub-reservoir　modular　networks　is　determined　by　sensitivity.　The　model　scale　adaptability　is　obtained　and　the　sub-reservoir　modular　networks　are　sorted　by　the　deflned　sensitivities.　Then,　the　number　of　requisite　sub-reservoir　modular　networks　is　calculated　by　the　model　scale　adaptability.　The　redundant　sub-reservoir　modular　networks　with　smaller　sensitivities　are　deleted.　In　the　pruning　process,　the　echo　state　property　can　be　guaranteed　without　posterior　scaling　of　the　weights.　The　simulation　results　show　that　the　proposed　method　can　design　the　compact　structure　of　ESN　efiectively　and　has　better　generalization　ability　and　robustness.　Copyright　©　2019　Acta　Automatica　Sinica.　All　rights　reserved.