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[2026-05-20]<\/mark><\/strong>
<\/mark>\u795d\u8d3a\u8bfe\u9898\u7ec4\u738b\u817e\u9704<\/strong>\u540c\u5b66(2022\u7ea7\u535a\u58eb\u751f)\u5173\u4e8e\u8fb9\u7f18\u7aef\u5168\u8109\u51b2\u795e\u7ecf\u5f62\u6001\u5904\u7406\u5668\u7814\u7a76\u8bba\u6587\u201cA Tiny Neuromorphic Processor Enabling On-Chip Spike-Based Learning for Edge Intelligent System\u201d<\/strong>\u88ab\u96c6\u6210\u7535\u8def\u8bbe\u8ba1\u9886\u57df\u56fd\u9645\u77e5\u540d\u671f\u520aIEEE Transactions on Very Large Scale Integration (VLSI) Systems<\/em><\/strong>\u63a5\u6536\uff0c\u5e76\u83b7\u5f97\u8bfe\u9898\u7ec4\u4e30\u539a\u5956\u52b1\u3002<\/mark>

[2026-05-06]<\/strong>
\u8bfe\u9898\u7ec4\u9648\u5955\u822a<\/strong>\u540c\u5b66\uff082024\u7ea7\u7855\u58eb\u751f\uff09\u8d74OPPO\uff08\u6df1\u5733\uff09\u5b9e\u4e60\uff0c\u62c5\u4efbAI\u6838\u5fc3\u90e8\u95e8\u5927\u6a21\u578b\u8f6f\u786c\u534f\u540c\u8bbe\u8ba1\u5c97\u4f4d\uff08\u56e0\u516c\u53f8\u4fdd\u5bc6\u8981\u6c42\uff0c\u65e0\u6cd5\u516c\u5e03\u5177\u4f53\u9ad8\u85aa\uff0c\u6b22\u8fce\u5728\u201c\u56e2\u961f\u6210\u5458\u201d\u9875\u9762\u4e2d\u8054\u7cfb\u5176\u672c\u4eba\u54a8\u8be2\uff09<\/mark>
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\u8bfe\u9898\u7ec4\u4f59\u9732<\/strong>\u540c\u5b66\uff082024\u7ea7\u7855\u58eb\u751f\uff09\u8d74\u8054\u82b8\u79d1\u6280\u6709\u9650\u516c\u53f8\uff08\u82cf\u5dde\uff09\uff0c\u5f00\u542f\u7b2c\u4e8c\u671f\u5b9e\u4e60\uff0c\u62c5\u4efb\u6570\u5b57\u82af\u7247\u8bbe\u8ba1\u5de5\u7a0b\u5e08\u5c97\u4f4d\uff08\u7ea68k\/\u6708\uff09<\/mark>

[2026-04-02]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u6768\u4f73\u9716<\/strong>\u540c\u5b66\uff082024\u7ea7\u7855\u58eb\u751f\uff09\u9ad8\u8d28\u91cf\u5b8c\u6210\u4e2d\u79d1\u9662\u534a\u5bfc\u4f53\u6240\u8054\u57f9\u8bfe\u9898\uff0c\u83b7\u5f97\u7532\u65b910\u4e07\u5143\u52b3\u52a1\u8d39\u8865\u8d34\u3002<\/mark>

[2026-03-06]<\/strong>
\u8bfe\u9898\u7ec4\u6e38\u4fca\u950b<\/strong>\u540c\u5b66\uff082025\u7ea7\u7855\u58eb\u751f\uff09\u3001\u5c39\u8363\u6770<\/strong>\u540c\u5b66\uff082025\u7ea7\u7855\u58eb\u751f\uff09<\/mark>\u63d0\u524d\u4e24\u5e74\u4e09\u4e2a\u6708\u8fbe\u5230\u5b66\u6821\u4e13\u4e1a\u578b\u7855\u58eb\u6bd5\u4e1a\u8981\u6c42<\/mark>

[2026-01-14]<\/strong>
\u8bfe\u9898\u7ec4\u9648\u5955\u822a<\/strong>\u540c\u5b66\uff082024\u7ea7\u7855\u58eb\u751f\uff09\u63d0\u524d\u4e00\u5e74\u4e94\u4e2a\u6708\u8fbe\u5230\u5b66\u6821\u5b66\u672f\u578b\u7855\u58eb\u6bd5\u4e1a\u8981\u6c42<\/mark>

[2025-10-29]<\/mark><\/strong>
\u8bfe\u9898\u7ec4\u4f59\u9732<\/strong>\u540c\u5b66\uff082024\u7ea7\u7855\u58eb\u751f\uff09\u8d74\u4e0a\u6d77\u827e\u4e3a\u7535\u5b50\u6280\u672f\u80a1\u4efd\u6709\u9650\u516c\u53f8\u5b9e\u4e60\uff0c\u62c5\u4efb\u6570\u5b57IC\u8bbe\u8ba1\u5c97\u4f4d<\/mark>

[2025-10-18]<\/mark><\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u949f\u6b63\u9752<\/strong>\u5148\u751f\uff082021\u7ea7\u5de5\u7a0b\u535a\u58eb\u751f\uff09\u548c\u6768\u4f73\u9716<\/strong>\u540c\u5b66\uff082024\u7ea7\u7855\u58eb\u751f\uff09\u5408\u4f5c\u5173\u4e8e\u201c\u9b54\u6cd5\u68d2-4\u4ee3\u201d\u795e\u7ecf\u5f62\u6001\u7247\u4e0a\u5b66\u4e60\u5904\u7406\u5668\u7684\u7814\u7a76\u8bba\u6587\u201cMorphBungee-Tiny: An Ultra-Low-Cost FPGA Implementation of Neuromorphic Architecture With High-Accuracy On-Chip E-Prop Learning\u201d<\/strong> \u88ab\u7535\u8def\u4e0e\u7cfb\u7edf\u9886\u57df\u56fd\u9645\u77e5\u540d\u671f\u520aIEEE Transactions On Circuits and Systems II: Express Briefs<\/em><\/strong>\u63a5\u6536\uff0c\u5e76\u83b7\u5f97\u8bfe\u9898\u7ec4\u4e30\u539a\u5956\u52b1\u3002<\/mark>

[2025-09-26]<\/mark><\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u738b\u79b9\u8f69<\/strong>\u540c\u5b66\uff082023\u7ea7\u7855\u58eb\u751f\uff09\u83b7\u5f97\u4e2d\u7535\u79d1\u82af\u7247\u6280\u672f\u6709\u9650\u516c\u53f82025\u5c4a\u6821\u56ed\u62db\u8058\u5f55\u7528\u610f\u5411\u51fd<\/mark>

[2025-09-18]<\/mark><\/strong>
\u8bfe\u9898\u7ec4\u4f59\u9732<\/strong>\u540c\u5b66\uff082024\u7ea7\u7855\u58eb\u751f\uff09\u63d0\u524d\u4e00\u5e74\u4e5d\u4e2a\u6708\u8fbe\u5230\u5b66\u6821\u4e13\u4e1a\u578b\u7855\u58eb\u751f\u6bd5\u4e1a\u8981\u6c42<\/mark><\/mark>

[2025-06-21]<\/strong><\/mark>
\u8bfe\u9898\u7ec4\u55bb\u5251\u4f9d<\/strong>\u540c\u5b66\uff082020\u7ea7\u76f4\u535a\u751f\uff09\u4e3b\u6301\u5e26\u961f\uff0c\u738b\u79b9\u8f69<\/strong>\u540c\u5b66\uff082023\u7ea7\u7855\u58eb\u751f\uff09\u3001\u5085\u7fd4<\/strong>\u540c\u5b66\uff082025\u7ea7\u535a\u58eb\u751f\u30012023\u7ea7\u7855\u58eb\u751f\uff09\u53c2\u4e0e\u7684\u201c\u9762\u5411\u9ad8\u80fd\u6548\u6ce8\u610f\u529b\u8ba1\u7b97\u7684\u5168\u6570\u5b57\u5b58\u5185\u8ba1\u7b97\u52a0\u901f\u5668\u201d\u9879\u76ee\u83b7\u5f97\u7b2c\u516b\u5c4a\u4e2d\u56fd\u7814\u7a76\u751f\u521b\u201c\u82af\u201d\u5927\u8d5b\u56e2\u961f\u4f18\u79c0\u5956\u3002<\/mark>

[2025-06-21]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u4f55\u4fca\u8d24<\/strong>\u540c\u5b66\uff082019\u7ea7\u535a\u58eb\u751f\uff09\u5173\u4e8e\u5927\u8bed\u8a00\u6a21\u578b\u89c6\u969c\u8f85\u52a9\u7684\u7814\u7a76\u8bba\u6587\u201cUsing ChatGPT To Generate Walking Directions\u2014Could It Potentially Help Visually Impaired With Micronavigation?\u201d<\/strong>\u5728\u89c6\u89c9\u79d1\u5b66\u9886\u57df\u56fd\u9645\u77e5\u540d\u671f\u520aTranslational Vision Science & Technology<\/strong><\/em>\u6210\u529f\u53d1\u8868\u3002<\/mark>

[2025-05-16]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u4f55\u4fca\u8d24<\/strong>\u540c\u5b66\uff082019\u7ea7\u535a\u58eb\u751f\uff09\u5173\u4e8e\u53ef\u91cd\u6784\u4eff\u8111\u795e\u7ecf\u5143\u7aef\u4fa7\u4eff\u751f\u89c6\u89c9\u82af\u7247\u7684\u7814\u7a76\u8bba\u6587“A Visual-Cortex-Mimetic Tiny Neuromorphic Vision Processor Based on Reconfigurable Cortical Neuron Unit”\u00a0<\/strong>\u88ab\u7535\u8def\u4e0e\u7cfb\u7edf\u9886\u57df\u56fd\u9645\u77e5\u540d\u671f\u520aIEEE Transactions On Circuits and Systems II: Express Briefs<\/em><\/strong>\u63a5\u6536\uff0c\u5e76\u83b7\u5f97\u8bfe\u9898\u7ec4\u4e30\u539a\u5956\u52b1\u3002<\/mark>

[2025-05-16]<\/mark><\/strong>
\u8bfe\u9898\u7ec4\u63a8\u8350\u6768\u4f73\u9716<\/strong>\u540c\u5b66\uff082024\u7ea7\u7855\u58eb\u751f\uff09\u8d74\u4e2d\u56fd\u79d1\u5b66\u9662\u534a\u5bfc\u4f53\u7814\u7a76\u6240\u201c\u534a\u5bfc\u4f53\u82af\u7247\u7269\u7406\u4e0e\u6280\u672f\u201d\u5168\u56fd\u91cd\u70b9\u5b9e\u9a8c\u5ba4\u8fdb\u884c\u8054\u5408\u57f9\u517b\uff082025.5-2025.11\uff09\uff0c\u4ece\u4e8b\u89c6\u89c9\u82af\u7247\u5e94\u7528\u7cfb\u7edf\u5f00\u53d1\u7814\u7a76\u3002<\/mark>

[2025-03-25]<\/strong>
\u8bfe\u9898\u7ec4\u738b\u4e3d<\/strong>\u540c\u5b66\uff082022\u7ea7\u7855\u58eb\u751f\uff09\u53d7\u9080\u53c2\u52a0\u91cd\u5e86\u5927\u5b66\u5fae\u7535\u5b50\u4e0e\u901a\u4fe1\u5de5\u7a0b\u5b66\u9662\u535a\u7855\u8bba\u575b\uff0c\u5206\u4eab\u65a9\u83b7\u591a\u5bb6\u77e5\u540d\u4f01\u4e1a\u5b9e\u4e60\u53ca\u6b63\u5f0foffer\u7684\u7ecf\u9a8c<\/strong>\u3002(<\/mark>http:\/\/www.ccee.cqu.edu.cn\/info\/1384\/7327.htm<\/a>)<\/mark>

[2025-01-12]<\/strong>
\u8bfe\u9898\u7ec4\u9648\u51a0\u5b87<\/strong>\u540c\u5b66\uff082024\u7ea7\u76f4\u535a\u751f\uff09\u76f4\u535a\u5165\u5b66\u534a\u5e74\u8fbe\u5230\u5b66\u6821\u5b66\u672f\u578b\u535a\u58eb\u751f\u6bd5\u4e1a\u57fa\u672c\u6761\u4ef6<\/mark><\/p>\n\n\n\n

[2025-01-12]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u9648\u51a0\u5b87<\/strong>\u540c\u5b66\uff082024\u7ea7\u76f4\u535a\u751f\uff09\u5173\u4e8e\u805a\u5408\u6807\u7b7e\u5b66\u4e60\u795e\u7ecf\u5f62\u6001\u5904\u7406\u82af\u7247\u7684\u7814\u7a76\u8bba\u6587“An Edge Neuromorphic Processor With High-Accuracy On-Chip Aggregate-Label Learning” <\/strong>\u88ab\u7535\u8def\u4e0e\u7cfb\u7edf\u9886\u57df\u56fd\u9645\u77e5\u540d\u671f\u520aIEEE Transactions On Circuits and Systems II: Express Briefs<\/em><\/strong>\u63a5\u6536\uff0c\u5e76\u83b7\u5f97\u8bfe\u9898\u7ec4\u4e30\u539a\u5956\u52b1\u3002<\/mark>

[2024-12-30] <\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u5085\u7fd4<\/strong>\u540c\u5b66\uff08\u539f2023\u7ea7\u7855\u58eb\u751f\uff09\u51ed\u501f\u524d\u671f\u4f18\u5f02\u7684\u5b66\u672f\u6210\u679c\uff0c\u987a\u5229\u901a\u8fc7\u7855\u8f6c\u535a\u7533\u8bf7\u8003\u6838\uff0c\u63d0\u524d\u5f00\u59cb\u653b\u8bfb\u535a\u58eb\u5b66\u4f4d<\/strong><\/mark><\/p>\n\n\n\n

[2024-11-14]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u5168\u4f53\u5b66\u672f\u578b\u535a\u58eb\u751f\u83b7\u5f97\u535a\u58eb\u5b66\u4e1a\u5956\u5b66\u91d11\u4e07\u5143<\/strong>\uff0c\u738b\u4e3d<\/strong>\uff082022\u7ea7\u7855\u58eb\u751f\uff09\u3001\u5085\u7fd4<\/strong>\uff082023\u7ea7\u7855\u58eb\u751f\uff09\u3001\u738b\u79b9\u8f69<\/strong>\uff082023\u7ea7\u7855\u58eb\u751f\uff09\u3001\u9648\u5955\u822a<\/strong>\uff082024\u7ea7\u7855\u58eb\u751f\uff09\u3001\u6768\u4f73\u9716<\/strong>\uff082024\u7ea7\u7855\u58eb\u751f\uff09\u3001\u5c24\u535a<\/strong>\uff082024\u7ea7\u7855\u58eb\u751f\uff09\u591a\u4f4d\u540c\u5b66\u83b7\u5f97\u7855\u58eb\u751f<\/strong>A\u7b49\u5b66\u4e1a\u5956\u5b66\u91d18\u5343\u5143<\/strong>

[2024-11-12]<\/strong><\/mark>
\u8bfe\u9898\u7ec4\u5085\u7fd4<\/strong>\u540c\u5b66\uff082023\u7ea7\u7855\u58eb\u751f\uff09\u4e3b\u6301\u5e26\u961f\u53c2\u4e0e\u7684\u7b2c\u4e8c\u5341\u4e00\u5c4a\u4e2d\u56fd\u7814\u7a76\u751f\u6570\u5b66\u5efa\u6a21\u7ade\u8d5b\u83b7\u5f97\u5168\u56fd\u4e09\u7b49\u5956\u3002<\/mark>

[2024-11-11]<\/strong>
\u8bfe\u9898\u7ec4\u738b\u79b9\u8f69<\/strong>\u540c\u5b66\uff082023\u7ea7\u7855\u58eb\u751f\uff09\u8d74\u4e2d\u56fd\u7535\u79d1\u82af\u7247\u6280\u672f\u7814\u7a76\u9662\u5b9e\u4e60\uff082024.11-2025.4\uff09\uff0c\u62c5\u4efb\u7cfb\u7edf\u4ea7\u54c1\u8bbe\u8ba1\u6280\u672f\u5c97\u3002

[2024-11-04]<\/strong><\/mark>
\u70ed\u70c8\u795d\u8d3a\u8bfe\u9898\u7ec4\u738b\u4e3d<\/strong>\u540c\u5b66\uff082022\u7ea7\u7855\u58eb\u751f\uff09\u83b7\u5f972\u4e07\u5143\u7814\u7a76\u751f\u56fd\u5bb6\u5956\u5b66\u91d1\uff0c\u5e76\u83b7\u8bfe\u9898\u7ec42000\u5143\u914d\u5957\u5956\u52b1\u3002<\/mark>

[2024-10-28]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u949f\u6b63\u9752<\/strong>\u5148\u751f\uff082021\u7ea7\u5de5\u7a0b\u535a\u58eb\uff09\u548c\u738b\u6d77\u51b0<\/strong>\u540c\u5b66\uff082023\u7ea7\u535a\u58eb\u751f\u30012020\u7ea7\u7855\u58eb\u751f\uff09\u5408\u4f5c\u5173\u4e8e\u7269\u7aef\u9ad8\u6027\u80fd\u795e\u7ecf\u5f62\u6001\u5904\u7406\u5668\u7684\u7814\u7a76\u8bba\u6587\u201cMorphBungee-Lite: An Edge Neuromorphic Architecture With Balanced Cross-Core Workloads Based on Layer-Wise Event-Batch Learning\/Inference<\/strong>\u201d\u88ab\u7535\u8def\u4e0e\u7cfb\u7edf\u9886\u57df\u56fd\u9645\u77e5\u540d\u671f\u520aIEEE Transactions On Circuits and Systems II: Express Briefs<\/em><\/strong>\u63a5\u6536\uff0c\u5e76\u83b7\u5f97\u8bfe\u9898\u7ec4\u4e30\u539a\u5956\u52b1\u3002

[2024-10-28]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u738b\u4e3d<\/strong>\u540c\u5b66\uff082022\u7ea7\u7855\u58eb\u751f\uff09\u83b7\u5f97\u4eac\u4e1c<\/strong>\u3001\u79d1\u5927\u8baf\u98de<\/strong>\u3001\u62fc\u591a\u591a<\/strong>2025\u5c4a\u6821\u56ed\u62db\u8058\u5f55\u7528\u610f\u5411\u51fd

[2024-10-18]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u4f55\u4fca\u8d24<\/strong>\u540c\u5b66\uff082019\u7ea7\u535a\u58eb\u751f\uff09\u5173\u4e8e\u7247\u4e0a\u591a\u5c42STDP\u5377\u79ef\u5b66\u4e60SNN\u82af\u7247\u7684\u8bba\u6587\u201cA Visual Cortex-Inspired Edge Neuromorphic Hardware Architecture With On-Chip Multi-Layer STDP Learning<\/strong>\u201d\u88abJCR\u4e00\u533a\u671f\u520aComputers and Electrical Engineering<\/em><\/strong>\u63a5\u6536\uff0c\u5e76\u83b7\u5f97\u8bfe\u9898\u7ec4\u4e30\u539a\u5956\u52b1\u3002

[2024-10-17]<\/strong>
<\/mark>\u795d\u8d3a\u8bfe\u9898\u7ec4\u5085\u7fd4<\/strong>\u540c\u5b66\uff082023\u7ea7\u7855\u58eb\u751f\uff09\u83b7\u5f97\u6765\u798f\u5956\u5b66\u91d15\u5343\u5143<\/strong>

[2024-10-16]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u738b\u4e3d<\/strong>\u540c\u5b66\uff082022\u7ea7\u7855\u58eb\u751f\uff09\u3001\u5085\u7fd4<\/strong>\u540c\u5b66\uff082023\u7ea7\u7855\u58eb\u751f\uff09\u8363\u83b7\u91cd\u5e86\u5927\u5b66\u4f18\u79c0\u7814\u7a76\u751f<\/strong>\u8868\u5f70

[2024-10-15]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u738b\u4e3d<\/strong>\u540c\u5b66\uff082022\u7ea7\u7855\u58eb\u751f\uff09\u5173\u4e8e\u4f4e\u5149\u7167\u56fe\u50cf\u53bb\u9a6c\u8d5b\u514b\u7684\u7814\u7a76\u8bba\u6587\u201cLLD-GAN: An End-to-End Network for Low-Light Image Demosaicking\u201d<\/strong>\u88abJCR\u4e00\u533a\u671f\u520aDisplays<\/em><\/strong>\u63a5\u6536\uff0c\u5e76\u83b7\u5f97\u8bfe\u9898\u7ec4\u4e30\u539a\u5956\u52b1\u3002<\/mark>

[2024-08-16]<\/mark><\/strong>
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[2024-06-22]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u5085\u7fd4<\/strong>\u540c\u5b66\uff082023\u7ea7\u7855\u58eb\u751f\uff09\u4e3b\u6301\u5e26\u961f\uff0c\u738b\u79b9\u8f69<\/strong>\u540c\u5b66\uff082023\u7ea7\u7855\u58eb\u751f\uff09\u3001\u9648\u51a0\u5b87<\/strong>\u540c\u5b66\uff082024\u7ea7\u76f4\u535a\u751f\uff09\u53c2\u4e0e\u7684\u201c\u4ece\u82af\u51fa\u53d1\uff0c\u4e07\u7269\u6709\u7075-\u9762\u5411\u8fb9\u7f18\u7aef\u8bbe\u5907\u7684\u795e\u7ecf\u5f62\u6001\u667a\u80fd\u8ba1\u7b97\u82af\u7247\u201d\u9879\u76ee\u83b7\u5f97\u7b2c\u516d\u5c4a\u201d\u5927\u521b\u6167\u8c37\u201c\u5927\u5b66\u751f\u521b\u4e1a\u521b\u65b0\u5927\u8d5b\u6570\u5b57\u7ecf\u6d4e\u4eba\u624d\u7ec4\u4e8c\u7b49\u5956<\/strong>\uff0c\u5e76\u83b7\u6bd4\u8d5b\u5956\u91d11.5\u4e07\u5143<\/strong>\u3002

[2024-06-21]<\/strong>
\u8bfe\u9898\u7ec4\u738b\u4e3d<\/strong>\u540c\u5b66\uff082022\u7ea7\u7855\u58eb\u751f\uff09\u559c\u83b7JDYoung Offer\uff0c\u5c06\u4e8e\u4e03\u6708\u521d\u8d74\u4eac\u4e1c\u5b9e\u4e60\uff0c\u62c5\u4efb\u6280\u672f\u4ea7\u54c1\u7ecf\u7406\u4e00\u804c\u3002

[2024-06-07]<\/strong>
\u8bfe\u9898\u7ec4\u738b\u817e\u9704<\/strong>\u540c\u5b66\uff082022\u7ea7\u535a\u58eb\u751f\u30012019\u7ea7\u7855\u58eb\u751f\uff09\u63d0\u524d\u4e24\u5e74\u8fbe\u5230\u5b66\u6821\u5b66\u672f\u578b\u535a\u58eb\u751f\u6bd5\u4e1a\u8981\u6c42<\/mark>

[2024-06-07]<\/strong>
\u70ed\u70c8\u795d\u8d3a\u8bfe\u9898\u7ec4\u738b\u817e\u9704<\/strong>\u540c\u5b66\uff082022\u7ea7\u535a\u58eb\u751f\u30012019\u7ea7\u7855\u58eb\u751f\uff09\u5173\u4e8e\u7269\u7aef\u9ad8\u6027\u80fd\u795e\u7ecf\u5f62\u6001\u5904\u7406\u5668\u7684\u7814\u7a76\u8bba\u6587\u201cMorphBungee: A 65-nm 7.2-mm2<\/sup> 27-\u03bcJ\/image Digital Edge Neuromorphic Chip with On-Chip 802-frame\/s Multi-Layer Spiking Neural Network Learning<\/strong>\u201d\u88ab\u7535\u8def\u4e0e\u7cfb\u7edf\u9886\u57df\u56fd\u9645\u77e5\u540d\u671f\u520aIEEE Transactions on Biomedical Circuits and Systems<\/em><\/strong>\u63a5\u6536\uff0c\u5e76\u83b7\u5f97\u8bfe\u9898\u7ec4\u4e30\u539a\u5956\u52b1

[2024-06-07]<\/strong>
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<\/p>\n\n\n\n

[2024-06-07]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u738b\u6d77\u51b0<\/strong>\u540c\u5b66\uff082023\u7ea7\u535a\u58eb\u751f\u30012020\u7ea7\u7855\u58eb\u751f\uff0c\u4e3b\u6301\u5e26\u961f\uff09\u3001\u6768\u4f73\u9716<\/strong>\u540c\u5b66\uff082024\u7ea7\u7855\u58eb\u751f\uff09\u6210\u529f\u7533\u8bf7\u7acb\u9879\u91cd\u5e86\u5927\u5b662024\u5e74\u91cd\u5e86\u5e02\u7814\u7a76\u751f\u79d1\u7814\u521b\u65b0\u9879\u76ee\uff08\u667a\u6167\u57ce\u5e02\u6280\u672f\u4e0e\u521b\u610f\u8bbe\u8ba1\u4e13\u9879\uff09<\/strong> \u201c\u7528\u4e8e\u4eba\u8138\u8bc6\u522b\u7684\u8f66\u8f7d\u667a\u80fd\u6444\u50cf\u5934\u7cfb\u7edf\u8bbe\u8ba1\u201d

[2024-06-07]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u5085\u7fd4<\/strong>\u540c\u5b66\uff082023\u7ea7\u7855\u58eb\u751f\uff0c\u4e3b\u6301\u5e26\u961f\uff09\u3001\u9ad8\u704f\u7136<\/strong>\u540c\u5b66\uff082021\u7ea7\u76f4\u535a\u751f\uff09\u3001\u738b\u79b9\u8f69<\/strong>\u540c\u5b66\uff082023\u7ea7\u7855\u58eb\u751f\uff09\u6210\u529f\u7533\u8bf7\u7acb\u9879\u91cd\u5e86\u5927\u5b662024\u5e74\u91cd\u5e86\u5e02\u7814\u7a76\u751f\u79d1\u7814\u521b\u65b0\u9879\u76ee\uff08\u667a\u6167\u57ce\u5e02\u6280\u672f\u4e0e\u521b\u610f\u8bbe\u8ba1\u4e13\u9879\uff09<\/strong> \u201c\u5b9e\u65f6\u7247\u4e0a\u4eba\u5f62\u68c0\u6d4b\u7cfb\u7edf\u201d

[2024-04-25]<\/strong>
\u8bfe\u9898\u7ec4\u5085\u7fd4<\/strong>\u540c\u5b66\uff082023\u7ea7\u7855\u58eb\u751f\uff09\u63d0\u524d\u4e24\u5e74\u4e8c\u4e2a\u6708\u8fbe\u5230\u5b66\u6821\u5b66\u672f\u578b\u7855\u58eb\u751f\u6bd5\u4e1a\u8981\u6c42<\/mark>

[2024-04-25]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u5085\u7fd4<\/strong>\u540c\u5b66\uff082023\u7ea7\u7855\u58eb\u751f\uff09\u5173\u4e8e\u5e7d\u7075\u6db2\u6001\u673a\u786c\u4ef6\u67b6\u6784\u7684\u7814\u7a76\u8bba\u6587\u201cGhost Reservoir: A Memory-Efficient Low-Power and Real-Time Neuromorphic Processor of Liquid State Machine with On-Chip Learning<\/strong>\u201d\u88ab\u7535\u8def\u4e0e\u7cfb\u7edf\u9886\u57df\u56fd\u9645\u77e5\u540d\u671f\u520aIEEE Transactions on Circuits and Systems II: Express Briefs<\/strong><\/em><\/em><\/strong>\u63a5\u6536\uff0c\u5e76\u83b7\u5f97\u8bfe\u9898\u7ec4\u4e30\u539a\u5956\u52b1\uff08\u7531\u8bfe\u9898\u7ec4\u7530\u654f<\/strong>\u8001\u5e08\u6307\u5bfc\uff09

[2024-04-22]<\/strong>
\u8bfe\u9898\u7ec4\u738b\u4e3d<\/strong>\u540c\u5b66\uff082022\u7ea7\u7855\u58eb\u751f\uff09\u8d74\u851a\u6765\u8f6f\u4ef6\u79d1\u6280\uff08\u4e0a\u6d77\uff09\u6709\u9650\u516c\u53f8\u5b9e\u4e60\uff0c\u62c5\u4efbAI\u4ea7\u54c1\u7ecf\u7406\u5c97\u4f4d

[2024-03-25]<\/strong>
\u8bfe\u9898\u7ec4\u738b\u4e3d<\/strong>\u540c\u5b66\uff082022\u7ea7\u7855\u58eb\u751f\uff09\u63d0\u524d\u4e00\u5e74\u4e09\u4e2a\u6708\u8fbe\u5230\u5b66\u6821\u5b66\u672f\u578b\u7855\u58eb\u751f\u6bd5\u4e1a\u8981\u6c42<\/mark>

[2023-11-15]<\/strong>
\u8bfe\u9898\u7ec4\u738b\u79b9\u8f69<\/strong>\u540c\u5b66\uff082023\u7ea7\u7855\u58eb\u751f\uff09\u63d0\u524d\u4e24\u5e74\u4e03\u4e2a\u6708\u8fbe\u5230\u5b66\u6821\u4e13\u4e1a\u578b\u7855\u58eb\u751f\u6bd5\u4e1a\u8981\u6c42<\/mark>

[2023-11-01]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u5168\u4f53\u535a\u58eb\u751f\u30012021\u7ea7\u30012022\u7ea7\u548c2023\u7ea7\u7855\u58eb\u751f\u5168\u5458\u83b7\u5f97A\u7b49\u5b66\u4e1a\u5956\u5b66\u91d1\uff08\u535a\u58eb\u751f1\u4e07\u5143\uff0c\u7855\u58eb\u751f8\u5343\u5143\uff09<\/strong>

[2023-09-20]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u5f20\u9756\u96c5<\/strong>\u540c\u5b66\uff082021\u7ea7\u7855\u58eb\u751f\uff09\u8363\u83b7\u91cd\u5e86\u5927\u5b66\u4f18\u79c0\u7814\u7a76\u751f<\/strong>\u548c\u91cd\u5e86\u5927\u5b66\u4f18\u79c0\u6bd5\u4e1a\u751f<\/strong>\u8868\u5f70\uff0c\u5eb9\u4e91\u9e4f<\/strong>\u540c\u5b66\uff082021\u7ea7\u7855\u58eb\u751f\uff09\u8363\u83b7\u91cd\u5e86\u5927\u5b66\u4f18\u79c0\u7814\u7a76\u751f<\/strong>\u8868\u5f70

[2023-08-29]<\/strong>
\u70ed\u70c8\u795d\u8d3a\u8bfe\u9898\u7ec4\u9648\u4e50\u6bc5<\/strong>\u540c\u5b66\uff082021\u7ea7\u7855\u58eb\u751f\uff09\u5173\u4e8e\u9ad8\u80fd\u6548\u89c6\u89c9\u82af\u7247\u5904\u7406\u5668\u8bbe\u8ba1\u7684\u7814\u7a76\u8bba\u6587\u201cAn 8-T Processing-in-Memory SRAM Cell-Based Pixel-Parallel Array Processor for Vision Chips<\/strong>\u201d\u88ab\u96c6\u6210\u7535\u8def\u9886\u57df\u9876\u7ea7\u671f\u520aIEEE Transactions on Circuits and Systems I: Regular Papers<\/em><\/strong>\u63a5\u6536\uff0c\u5e76\u83b7\u5f97\u8bfe\u9898\u7ec4\u4e30\u539a\u5956\u52b1\uff08\u7531\u8bfe\u9898\u7ec4\u7530\u654f<\/strong>\u8001\u5e08\u6307\u5bfc\uff09

[2023-08-08]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u738b\u817e\u9704<\/strong>\u540c\u5b66\uff082022\u7ea7\u535a\u58eb\u751f\u30012019\u7ea7\u7855\u58eb\u751f\uff09\u5173\u4e8e\u7247\u4e0a\u6df1\u5ea6\u5b66\u4e60\u7c7b\u8111\u82af\u7247\u8bbe\u8ba1\u7684\u7814\u7a76\u8bba\u6587\u88ab\u96c6\u6210\u7535\u8def\u8bbe\u8ba1\u9886\u57df\u56fd\u9645\u4e00\u6d41\u4f1a\u8baeA-SSCC<\/em><\/strong>\u63a5\u6536\uff0c\u5e76\u83b7\u5f97\u8bfe\u9898\u7ec4\u5956\u52b1

[2023-07-14]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u4f55\u4fca\u8d24<\/strong>\u540c\u5b66\uff082019\u7ea7\u535a\u58eb\u751f\uff09\u6210\u529f\u7533\u8bf7\u5e76\u4e3b\u6301\u201c\u91cd\u5e86\u5927\u5b66\u901a\u4fe1\u5b66\u9662-\u4e0a\u6d77\u7075\u7280\u6821\u4f01\u5408\u4f5c\u4e2d\u5fc3\u201d\u7814\u7a76\u751f\u5f00\u653e\u8bfe\u9898\u201c\u9ad8\u7cbe\u5ea6\u7684\u6fc0\u5149\u4e2d\u5fc3\u7ebf\u63d0\u53d6\u7b97\u6cd5\u201d\uff08\u7ecf\u8d39\uff1a1\u4e07\u5143<\/strong>\uff09

[2023-06-30]<\/strong>
\u8bfe\u9898\u7ec4\u63a8\u8350\u9648\u4e50\u6bc5<\/strong>\u540c\u5b66\uff082021\u7ea7\u7855\u58eb\u751f\uff09\u8d74\u4e4b\u6c5f\u5b9e\u9a8c\u5ba4\u5b9e\u4e60\uff0c\u62c5\u4efbIC\u8bbe\u8ba1\u5de5\u7a0b\u5e08\u5c97\u4f4d

[2023-05-30]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u5f20\u9756\u96c5<\/strong>\u540c\u5b66\uff082021\u7ea7\u7855\u58eb\u751f\uff09\u6210\u529f\u7533\u8bf7\u5e76\u4e3b\u6301\u91cd\u5e86\u5e02\u7814\u7a76\u751f\u79d1\u7814\u521b\u65b0\u9879\u76ee<\/strong>\u201c\u9762\u5411\u8fb9\u7f18\u7aef\u667a\u80fd\u8f66\u8f7d\u8eab\u4efd\u8bc6\u522b\u7cfb\u7edf\u7684SNN\u5904\u7406\u5668\u8bbe\u8ba1\u201d

[2023-05-23]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u738b\u6d77\u51b0<\/strong>\u540c\u5b66\uff082020\u7ea7\u7855\u58eb\u751f\uff09\u51ed\u501f\u4f18\u5f02\u7684\u79d1\u7814\u5b66\u672f\u6210\u679c\uff0c\u987a\u5229\u901a\u8fc7\u91cd\u5e86\u5927\u5b66\u535a\u58eb\u751f\u5165\u5b66\u7533\u8bf7\u8003\u6838\uff0c\u7ee7\u7eed\u5728\u7ec4\u5185\u653b\u8bfb\u535a\u58eb\u5b66\u4f4d

[2023-02-24]<\/strong>
\u8bfe\u9898\u7ec4\u5eb9\u4e91\u9e4f<\/strong>\u540c\u5b66\uff082021\u7ea7\u7855\u58eb\u751f\uff09\u63d0\u524d\u4e00\u5e74\u56db\u4e2a\u6708\u8fbe\u5230\u5b66\u6821\u4e13\u4e1a\u578b\u7855\u58eb\u751f\u6bd5\u4e1a\u8981\u6c42<\/mark>

[2023-01-19]<\/strong>
\u8bfe\u9898\u7ec4\u5f20\u9756\u96c5<\/strong>\u540c\u5b66\uff082021\u7ea7\u7855\u58eb\u751f\uff09\u63d0\u524d\u4e00\u5e74\u4e94\u4e2a\u6708\u8fbe\u5230\u5b66\u6821\u4e13\u4e1a\u578b\u7855\u58eb\u751f\u6bd5\u4e1a\u8981\u6c42<\/mark>

[2023-01-19]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u5f20\u9756\u96c5<\/strong>\u540c\u5b66\uff082021\u7ea7\u7855\u58eb\u751f\uff09\u5173\u4e8e\u538b\u7f29\u611f\u77e5\u7c7b\u8111\u82af\u7247\u8bbe\u8ba1\u7684\u7814\u7a76\u8bba\u6587\u201cAn Edge Neuromorphic Hardware with Fast On-Chip Error-Triggered Learning on Compressive Sensed Spikes<\/strong>\u201d\u88ab\u7535\u8def\u4e0e\u7cfb\u7edf\u9886\u57df\u56fd\u9645\u77e5\u540d\u671f\u520aIEEE Transactions on Circuits and Systems II: Express Briefs<\/strong><\/em>\u63a5\u6536\uff0c\u5e76\u83b7\u5f97\u8bfe\u9898\u7ec4\u4e30\u539a\u5956\u52b1

[2022-12-28]<\/strong>
\u8bfe\u9898\u7ec4\u9648\u601d\u8c6a<\/strong>\u540c\u5b66\uff082021\u7ea7\u7855\u58eb\u751f\uff09\u63d0\u524d\u4e00\u5e74\u516d\u4e2a\u6708\u8fbe\u5230\u5b66\u6821\u4e13\u4e1a\u578b\u7855\u58eb\u751f\u6bd5\u4e1a\u8981\u6c42<\/mark>

[2022-11-21]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u5362\u9756<\/strong>\u540c\u5b66\uff082020\u7ea7\u7855\u58eb\u751f\uff09\u8363\u83b7\u91cd\u5e86\u5927\u5b66\u4f18\u79c0\u5b66\u751f<\/strong>\u8868\u5f70

[2022-11-13]<\/strong>
\u8bfe\u9898\u7ec4\u9648\u4e50\u6bc5<\/strong>\u540c\u5b66\uff082021\u7ea7\u7855\u58eb\u751f\uff09\u63d0\u524d\u4e00\u5e74\u4e03\u4e2a\u6708\u8fbe\u5230\u5b66\u6821\u4e13\u4e1a\u578b\u7855\u58eb\u751f\u6bd5\u4e1a\u8981\u6c42<\/mark><\/p>\n\n\n\n

[2022-11-13]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u9648\u4e50\u6bc5<\/strong>\u540c\u5b66\uff082021\u7ea7\u7855\u58eb\u751f\uff092022\u5e74IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)<\/em><\/strong>\u4f1a\u8bae\u8bba\u6587\u83b7\u5f97Best Paper Award<\/strong>\uff08\u7531\u8bfe\u9898\u7ec4\u7530\u654f<\/strong>\u8001\u5e08\u6307\u5bfc\uff09<\/p>\n\n\n\n

[2022-11-13]<\/strong>
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[2022-10-31]<\/strong>
\u70ed\u70c8\u795d\u8d3a\u8bfe\u9898\u7ec4\u738b\u6d77\u51b0<\/strong>\u540c\u5b66\uff082020\u7ea7\u7855\u58eb\u751f\uff09\u83b7\u5f972\u4e07\u5143\u7814\u7a76\u751f\u56fd\u5bb6\u5956\u5b66\u91d1<\/strong>\uff082020\u7ea7\u4e13\u7855\u6392\u540d2\/79\uff09<\/p>\n\n\n\n

[2022-09-30]<\/strong>
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[2022-09-09] <\/strong>
\u8bfe\u9898\u7ec4\u63a8\u8350\u55bb\u5251\u4f9d<\/strong>\u540c\u5b66\uff082020\u7ea7\u76f4\u535a\u751f\uff09\u8d74\u6e05\u534e\u5927\u5b66<\/strong>\u7535\u5b50\u5de5\u7a0b\u7cfb\u667a\u80fd\u611f\u77e5\u96c6\u6210\u7535\u8def\u4e0e\u7cfb\u7edf\u5b9e\u9a8c\u5ba4\uff0c\u5f00\u5c55\u957f\u671f\u8054\u5408\u57f9\u517b\u79d1\u7814\u5de5\u4f5c<\/p>\n\n\n\n

[2022-08-30] <\/strong>
\u8bfe\u9898\u7ec4\u63a8\u8350\u9648\u601d\u8c6a<\/strong><\/mark>\u540c\u5b66\uff082021\u7ea7\u7855\u58eb\u751f\uff09\u8d74\u4e0a\u6d77\u7280\u7075\u89c6\u89c9\u79d1\u6280\u6709\u9650\u516c\u53f8\uff08\u6210\u90fd\u5206\u516c\u53f8\uff09\u5b9e\u4e60\uff0c\u62c5\u4efb\u6570\u5b57IC\u524d\u7aef\u8bbe\u8ba1\u53ca\u9a8c\u8bc1\u5c97\u4f4d<\/p>\n\n\n\n

[2022-08-13]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u738b\u6d77\u51b0<\/strong>\u540c\u5b66\uff082020\u7ea7\u7855\u58eb\u751f\uff09\u3001\u5362\u9756<\/strong>\u540c\u5b66\uff082020\u7ea7\u7855\u58eb\u751f\uff09\u548c\u5f20\u9756\u96c5<\/strong>\u540c\u5b66\uff082021\u7ea7\u7855\u58eb\u751f\uff09\u83b7\u5f97\u201c\u534e\u4e3a\u676f\u201d\u7b2c\u4e94\u5c4a\u4e2d\u56fd\u7814\u7a76\u751f\u521b\u201c\u82af\u201d\u5927\u8d5b\u51b3\u8d5b\u5168\u56fd\u4e09\u7b49\u5956<\/strong><\/p>\n\n\n\n

[2022-07-05]<\/strong>
\u70ed\u70c8\u795d\u8d3a\u8bfe\u9898\u7ec4\u738b\u6d77\u51b0<\/strong>\u540c\u5b66\uff082020\u7ea7\u7855\u58eb\u751f\uff09\u5173\u4e8e\u8f7b\u91cf\u7ea7\u4e09\u91cd\u7c7b\u8111\u795e\u7ecf\u5f62\u6001\u82af\u7247\u8bbe\u8ba1\u7684\u7814\u7a76\u8bba\u6587\u201cTripleBrain: A Compact Neuromorphic Hardware Core with Fast On-Chip Self-Organizing and Reinforcement Spike-Timing Dependent Plasticity<\/strong>\u201d\u88ab\u7535\u8def\u4e0e\u7cfb\u7edf\u9886\u57df\u56fd\u9645\u77e5\u540d\u671f\u520aIEEE Transactions on Biomedical Circuits and Systems<\/em><\/strong>\u63a5\u6536\uff0c\u5e76\u83b7\u5f97\u8bfe\u9898\u7ec4\u4e30\u539a\u5956\u52b1<\/p>\n\n\n\n

[2022-06-29]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u738b\u817e\u9704<\/strong>\u540c\u5b66\uff082019\u7ea7\u7855\u58eb\u751f\uff09\u51ed\u501f\u4f18\u5f02\u7684\u79d1\u7814\u5b66\u672f\u6210\u679c\uff0c\u987a\u5229\u901a\u8fc7\u91cd\u5e86\u5927\u5b66\u535a\u58eb\u751f\u5165\u5b66\u7533\u8bf7\u8003\u6838\uff0c\u7ee7\u7eed\u5728\u7ec4\u5185\u653b\u8bfb\u535a\u58eb\u5b66\u4f4d<\/p>\n\n\n\n

[2022-06-20] <\/strong>
\u8bfe\u9898\u7ec4\u63a8\u8350\u55bb\u5251\u4f9d<\/strong><\/mark>\u540c\u5b66\uff082020\u7ea7\u76f4\u535a\u751f\uff09\u3001\u5362\u9756<\/strong>\u540c\u5b66\uff082020\u7ea7\u7855\u58eb\u751f\uff09\u8d74\u676d\u5dde\u6d77\u5eb7\u5a01\u89c6\u516c\u53f8\u5b9e\u4e60\uff0c\u62c5\u4efb\u82af\u7247\u8bbe\u8ba1\u5de5\u7a0b\u5e08\u5c97\u4f4d<\/p>\n\n\n\n

[2022-06-15]<\/strong>
\u8bfe\u9898\u7ec4\u6307\u5bfc\u7684\u56fd\u5bb6\u7ea7<\/strong>\u5927\u5b66\u751f\u521b\u65b0\u8bad\u7ec3\u9879\u76ee\u201c\u8f7b\u91cf\u5316\u4e09\u91cd\u7c7b\u8111\u795e\u7ecf\u7f51\u7edc\u7814\u7a76\u201d\u83b7\u5f97\u4f18\u79c0\u7ed3\u9898<\/strong><\/p>\n\n\n\n

[2022-04-02]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u4f55\u4fca\u8d24<\/strong>\u540c\u5b66\uff082019\u7ea7\u535a\u58eb\u751f\uff09\u5173\u4e8e\u6df7\u5408\u667a\u80fd\u89c6\u89c9\u8fd0\u52a8\u611f\u77e5\u82af\u7247\u8bbe\u8ba1\u7684\u7814\u7a76\u8bba\u6587\u201cLow-Cost Real-Time VLSI System for High Accuracy Optical Flow Estimation Using Biological Motion Features and Random Forests\u201d<\/strong>\u88abSCI\u671f\u520a\u3001\u4fe1\u606f\u5b66\u79d1\u9886\u57df\u552f\u4e00\u5165\u9009\u4e2d\u56fd\u79d1\u6280\u671f\u520a\u5353\u8d8a\u884c\u52a8\u8ba1\u5212\u671f\u520aScience China Information Sciences<\/strong><\/em>\u63a5\u6536\uff0c\u5e76\u83b7\u5f97\u8bfe\u9898\u7ec4\u5956\u52b1<\/p>\n\n\n\n

[2022-03-10]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u4f55\u4fca\u8d24<\/strong>\u540c\u5b66\uff082019\u7ea7\u535a\u58eb\u751f\uff09\u4e3b\u6301\u5e26\u961f\u7684\u201c\u7247\u4e0a\u5b9e\u65f6\u6df1\u5ea6\u5b66\u4e60\u795e\u7ecf\u5f62\u6001\u7c7b\u8111\u82af\u7247\u201d\u9879\u76ee\u5165\u9009\u7b2c\u516b\u5c4a\u4e2d\u56fd\u56fd\u9645\u201c\u4e92\u8054\u7f51+\u201d\u5927\u5b66\u751f\u521b\u65b0\u521b\u4e1a\u5927\u8d5b\u91cd\u5e86\u5927\u5b66\u91cd\u70b9\u57f9\u80b2\u7acb\u9879\uff0c\u83b7\u5f971\u4e07\u5143\u8d44\u52a9<\/strong><\/p>\n\n\n\n

[2021-12-26]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u738b\u817e\u9704<\/strong>\u540c\u5b66\uff082019\u7ea7\u7855\u58eb\u751f\uff09\u5e26\u961f\u83b7\u5f97\u201c\u534e\u4e3a\u676f\u201d\u7b2c\u56db\u5c4a\u4e2d\u56fd\u7814\u7a76\u751f\u521b\u201c\u82af\u201d\u5927\u8d5b\u51b3\u8d5b\u5168\u56fd\u4e8c\u7b49\u5956\uff0c<\/strong>\u5e76\u83b7\u5f97\u5927\u8d5b8\u5343\u5143\u5956\u52b1<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u6768\u6676<\/strong>\u540c\u5b66\uff082019\u7ea7\u7855\u58eb\u751f\uff09\u3001\u674e\u777f<\/strong>\u540c\u5b66\uff082019\u7ea7\u7855\u58eb\u751f\uff09\u83b7\u5f97\u201c\u534e\u4e3a\u676f\u201d\u7b2c\u56db\u5c4a\u4e2d\u56fd\u7814\u7a76\u751f\u521b\u201c\u82af\u201d\u5927\u8d5b\u51b3\u8d5b\u5168\u56fd\u4e09\u7b49\u5956<\/strong><\/p>\n\n\n\n

[2021-10-28]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u5168\u4f53\u535a\u58eb\u751f\u30012019\u7ea7\u548c2020\u7ea7\u7855\u58eb\u751f\u5168\u5458\u83b7\u5f97A\u7b49\u5b66\u4e1a\u5956\u5b66\u91d1\uff08\u535a\u58eb\u751f1\u4e07\u5143\uff0c\u7855\u58eb\u751f8\u5343\u5143\uff09<\/strong><\/p>\n\n\n\n

[2021-10-21]<\/strong>
\u70ed\u70c8\u795d\u8d3a\u8bfe\u9898\u7ec4\u6768\u6676<\/strong>\u540c\u5b66\uff082019\u7ea7\u7855\u58eb\u751f\uff09\u83b7\u5f972\u4e07\u5143\u7814\u7a76\u751f\u56fd\u5bb6\u5956\u5b66\u91d1<\/strong>\uff08\u5b66\u9662\u6392\u540d2\/165\uff09<\/p>\n\n\n\n

[2021-10-18]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u7530\u654f\u8001\u5e08<\/strong>\u6210\u529f\u7533\u8bf7\u83b7\u5f972021\u5e74\u5ea6CCF-\u6d77\u5eb7\u5a01\u89c6\u6591\u5934\u96c1\u57fa\u91d1\u8d44\u52a9\u9879\u76ee<\/strong>\u201c\u57fa\u4e8eSRAM\u7684\u9ad8\u80fd\u6548\u5b58\u5185\u8ba1\u7b97\u7814\u7a76\u201d\uff0827\u4e07<\/strong>\uff09<\/p>\n\n\n\n

[2021-10-08]<\/strong>
\u8bfe\u9898\u7ec4\u63a8\u8350\u5eb9\u4e91\u9e4f<\/strong>\u540c\u5b66\uff082021\u7ea7\u7855\u58eb\u751f\uff09\u8d74\u91cd\u5e86\u5148\u950b\u6e1d\u5dde\u7535\u5668\u6709\u9650\u516c\u53f8\u5b9e\u4e60\uff0c\u8fdb\u884c\u957f\u671f\u4ea7\u5b66\u7ed3\u5408\u7814\u7a76\u5de5\u4f5c<\/p>\n\n\n\n

[2021-10-01]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u4f55\u796f<\/strong>\u540c\u5b66\uff082018\u7ea7\u672c\u79d1\u5b9e\u4e60\u751f\uff09\u5173\u4e8e\u7c7b\u8111\u795e\u7ecf\u7f51\u7edc\u82af\u7247\u8bbe\u8ba1\u7684\u7814\u7a76\u8bba\u6587\u201cA Low-cost FPGA Implementation of Spiking Extreme Learning Machine With On-chip Reward-Modulated STDP Learning<\/strong>\u201d\u88ab\u7535\u8def\u4e0e\u7cfb\u7edf\u9886\u57df\u56fd\u9645\u77e5\u540d\u671f\u520aIEEE Transactions on Circuits and Systems II: Express Briefs<\/strong><\/em>\u63a5\u6536\uff0c\u5e76\u83b7\u5f97\u8bfe\u9898\u7ec4\u4e30\u539a\u5956\u52b1<\/p>\n\n\n\n

[2021-09-27]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u7530\u654f\u8001\u5e08<\/strong>\u6210\u529f\u7acb\u9879\u91cd\u5e86\u5e02\u535a\u58eb\u540e\u79d1\u5b66\u57fa\u91d1\u9879\u76ee<\/strong>\u201c\u57fa\u4e8e\u5fc6\u963b\u5668\u7684\u8109\u51b2\u795e\u7ecf\u7f51\u7edc\u7247\u4e0a\u5b66\u4e60\u7535\u8def\u8bbe\u8ba1\u7814\u7a76\u201d<\/p>\n\n\n\n

[2021-09-25]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u4f55\u796f<\/strong>\u540c\u5b66\uff082018\u7ea7\u672c\u79d1\u5b9e\u4e60\u751f\uff09\u6210\u529f\u83b7\u5f97\u6e05\u534e\u5927\u5b66<\/strong>\u96c6\u6210\u7535\u8def\u5b66\u9662\u76f4\u535a<\/strong>\u8d44\u683c<\/p>\n\n\n\n

[2021-03-02]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u738b\u817e\u9704<\/strong>\u540c\u5b66\uff082019\u7ea7\u7855\u58eb\u751f\uff09\u8109\u51b2\u795e\u7ecf\u7f51\u7edc\u6df1\u5ea6\u5b66\u4e60\u7684\u7b97\u6cd5\u7814\u7a76\u8bba\u6587\u201cDeepTempo: a Hardware-Friendly Direct Feedback Alignment Multi-Layer Tempotron Learning Rule for Deep Spiking Neural Networks<\/strong>\u201d\u88ab\u7535\u8def\u4e0e\u7cfb\u7edf\u9886\u57df\u56fd\u9645\u77e5\u540d\u671f\u520aIEEE Transactions on Circuits and Systems II: Express Briefs<\/strong><\/em>\u63a5\u6536\uff0c\u5e76\u83b7\u5f97\u8bfe\u9898\u7ec4\u4e30\u539a\u5956\u52b1<\/p>\n\n\n\n

[2021-01-30]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u738b\u817e\u9704<\/strong>\u540c\u5b66\uff082019\u7ea7\u7855\u58eb\u751f\uff09\u8109\u51b2\u795e\u7ecf\u7f51\u7edc\u6df1\u5ea6\u5b66\u4e60\u7684\u7b97\u6cd5\u7814\u7a76\u8bba\u6587\u201cDeepTempo: a Hardware-Friendly Direct Feedback Alignment Multi-Layer Tempotron Learning Rule for Deep Spiking Neural Networks<\/strong>\u201d\u88ab\u56fd\u9645\u7535\u8def\u4e0e\u7cfb\u7edf\u5927\u4f1aIEEE International Symposium on Circuits & Systems (ISCAS 2021)<\/strong><\/em>\u63a5\u6536\uff0c\u5e76\u88ab\u9080\u8bf7\u6295\u7a3f<\/strong>\u81f3\u7535\u8def\u4e0e\u7cfb\u7edf\u9886\u57df\u56fd\u9645\u77e5\u540d\u671f\u520aIEEE Transactions on Circuits and Systems II: Express Briefs<\/strong><\/em>\uff0c\u83b7\u5f97\u8bfe\u9898\u7ec4\u5956\u52b1<\/p>\n\n\n\n

[2020-11-17]<\/strong>
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[2020-11-13]<\/strong>
\u8bfe\u9898\u7ec4\u63a8\u8350\u674e\u777f<\/strong>\u540c\u5b66\uff082019\u7ea7\u7855\u58eb\u751f\uff09\u8d74\u4e2d\u56fd\u79d1\u5b66\u9662\u8ba1\u7b97\u6280\u672f\u7814\u7a76\u6240\u8fdb\u884c\u4e3a\u671f\u4e00\u5e74\u8bbf\u5b66\u4ea4\u6d41\uff0c\u5e76\u62c5\u4efb\u4e2d\u79d1\u9662\u8ba1\u7b97\u6240\u8ba1\u7b97\u673a\u4f53\u7cfb\u7ed3\u6784\u56fd\u5bb6\u91cd\u70b9\u5b9e\u9a8c\u5ba4\u5ba2\u5ea7\u7814\u7a76\u52a9\u7406<\/strong><\/p>\n\n\n\n

[2020-11-10]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u738b\u817e\u9704<\/strong>\u540c\u5b66\uff082019\u7ea7\u7855\u58eb\u751f\uff09\u5173\u4e8e\u8109\u51b2\u795e\u7ecf\u7f51\u7edc\u7b97\u6cd5\u7684\u5b66\u672f\u8bba\u6587\u201cCompSNN: A Lightweight Spiking Neural Network Based on Spatiotemporally Compressive Spike Features<\/strong>\u201d\u88abSCI\u671f\u520a\u5f55\u7528\uff0c\u5e76\u83b7\u5f97\u8bfe\u9898\u7ec4\u5956\u52b1<\/p>\n\n\n\n

[2020-11-07]<\/strong>
\u70ed\u70c8\u795d\u8d3a\u8bfe\u9898\u7ec4\u9ec4\u8fdb\u56fd<\/strong>\u540c\u5b66\uff082018\u7ea7\u7855\u58eb\u751f\uff09\u51ed\u501f\u5728\u8bfb\u671f\u95f4\u4f18\u5f02\u7684\u8bba\u6587\u6210\u679c\uff0c\u7834\u683c\u83b7\u5f97\u666e\u901a\u516c\u529e\u9ad8\u6821\u6559\u7814\u5c97offer<\/strong><\/p>\n\n\n\n

[2020-10-23]<\/strong>
\u70ed\u70c8\u795d\u8d3a\u8bfe\u9898\u7ec4\u5f20\u6770<\/strong>\u540c\u5b66\uff082018\u7ea7\u7855\u58eb\u751f\uff09\u83b7\u5f972\u4e07\u5143\u7814\u7a76\u751f\u56fd\u5bb6\u5956\u5b66\u91d1<\/strong>\uff08\u6309\u8bba\u6587\u6210\u679c+\u9879\u76ee\u4e3b\u6301+\u7ade\u8d5b\u83b7\u5956\u7efc\u5408\u6392\u540d\uff0c\u5168\u5b66\u9662\u5e74\u7ea7\u7b2c2\uff09<\/p>\n\n\n\n

[2020-09-01]<\/strong>
\u795d\u8d3a\u8bfe\u9898\u7ec4\u5f20\u6770<\/strong>\u540c\u5b66\uff082018\u7ea7\u7855\u58eb\u751f\uff09\u5173\u4e8e\u56fe\u50cf\u76ee\u6807\u8ddf\u8e2a\u82af\u7247\u8bbe\u8ba1\u7684\u5b66\u672f\u8bba\u6587\u201cA Low-cost High-speed Object Tracking VLSI System Based on Unified Textural and Dynamic Compressive Features<\/strong>\u201d\u88ab\u7535\u8def\u4e0e\u7cfb\u7edf\u9886\u57df\u56fd\u9645\u77e5\u540d\u671f\u520a IEEE Transactions on Circuits and Systems II: Express Briefs <\/em><\/strong>\u5f55\u7528\uff0c\u5e76\u83b7\u5f97\u8bfe\u9898\u7ec4\u4e30\u539a\u5956\u52b1<\/p>\n\n\n\n

[2020-08-16]<\/strong>
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[2020-06-20] <\/strong>
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[2026-05-20]\u795d\u8d3a\u8bfe […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-13","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/pages\/13","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/comments?post=13"}],"version-history":[{"count":156,"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/pages\/13\/revisions"}],"predecessor-version":[{"id":2715,"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/pages\/13\/revisions\/2715"}],"wp:attachment":[{"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/media?parent=13"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}