This　paper　aims　to　propose　a　more　efficient　algorithm　for　the　multi-dimensional　classifier　design.　A　novel　model　of　wavelet　fuzzy　brain　emotional　learning　neural　network　(WFBELNN)　is　proposed.　This　model　comprises　a　wavelet　function,　a　fuzzy　inference　system　and　a　brain　emotional　learning　neural　network.　As　a　result,　the　learning　speed　and　the　classifying　accuracy　can　be　effectively　improved　by　the　proposed　model.　The　structure　of　WFBELNN　is　constructed　first,　and　then　the　gradient-descent　method　is　used　to　online　tune　the　parameters　of　WFBELNN.　Finally　a　medical　pattern　recognition　system　is　studied　to　verify　that　the　accurate　multi-dimensional　pattern　recognition　can　be　achieved　by　using　the　proposed　model.　A　comparison　between　the　proposed　WFBELNN　and　other　models　shows　that　the　proposed　model　can　achieve　the　most　accurate　classification　of　the　medical　pattern　recognition　and　it　is　also　more　suitable　to　deal　with　the　influence　of　the　uncertainties.　©　2019　-　IOS　Press　and　the　authors.　All　rights　reserved