A　neural　network　integrated　classifier　(NNIC)　designed　with　a　new　modulation　recognition　algorithm　based　on　the　decision-making　tree　is　proposed　in　this　paper.　Firstly,　instantaneous　parameters　are　extracted　in　the　time　domain　by　the　coordinated　rotation　digital　computer　(CORDIC)　algorithm　based　on　the　extended　convergence　domain　and　feature　parameters　of　frequency　spectrum　and　power　spectrum　are　extracted　by　the　time-frequency　analysis　method.　All　pattern　identification　parameters　are　calculated　under　the　I/Q　orthogonal　two-channel　structure,　and　constructed　into　the　feature　vector　set.　Next,　the　classifier　is　designed　according　to　the　modulation　pattern　and　recognition　performance　of　the　feature　parameter　set,　the　optimum　threshold　is　selected　for　each　feature　parameter　based　on　the　decision-making　mechanism　in　a　single　classifier,　multi-source　information　fusion　and　modulation　recognition　are　realized　based　on　feature　parameter　judge　process　in　the　NNIC.　Simulation　results　show　NNIC　is　competent　for　all　modulation　recognitions,　8　kinds　of　digital　modulated　signals　are　effectively　identified,　which　shows　the　recognition　rate　and　anti-interference　capability　at　low　SNR　are　improved　greatly,　the　overall　recognition　rate　can　reach　100%　when　SNR　is　12　dB.　Copyright　©　by　HIGH　TECHNOLOGY　LETTERS　PRESS.