In　recent　years,　face　recognition　technology　has　been　widely　used　in　security,　finance,　media　data　retrieval　and　other　fields　due　to　its　convenience,　concealment,　and　stability,　and　has　become　a　popular　research　field　in　various　scientific　research　institutions.　Among　them,　face　recognition　under　complex　conditions　under　different　lighting,　different　expressions,　and　partial　occlusion　has　become　a　research　hotspot.　Sparse　representation　algorithm,　as　the　mainstream　algorithm　to　solve　the　problem　of　face　recognition　under　complex　conditions,　although　it　improves　the　recognition　accuracy　compared　with　other　algorithms,　there　is　still　room　for　improvement.　Aiming　at　the　partial　occlusion　problem　in　face　recognition,　this　paper　conducted　many　experiments　under　different　training　samples　through　the　sparse　representation　algorithm　of　fusion　error.　The　experimental　results　show　that　the　algorithm　improves　the　recognition　rate　and　provides　a　new　solution　for　the　problem　of　face　recognition　under　partial　occlusion.　©　Published　under　licence　by　IOP　Publishing　Ltd.