{"id":251,"date":"2022-07-17T10:45:39","date_gmt":"2022-07-17T02:45:39","guid":{"rendered":"https:\/\/www.corticalchip.com\/?p=251"},"modified":"2026-01-28T20:38:09","modified_gmt":"2026-01-28T12:38:09","slug":"%e9%ab%98%e7%81%8f%e7%84%b6%e4%b8%aa%e4%ba%ba%e7%ae%80%e4%bb%8b","status":"publish","type":"post","link":"https:\/\/www.corticalchip.com\/index.php\/2022\/07\/17\/%e9%ab%98%e7%81%8f%e7%84%b6%e4%b8%aa%e4%ba%ba%e7%ae%80%e4%bb%8b\/","title":{"rendered":"\u9ad8\u704f\u7136\u4e2a\u4eba\u7b80\u4ecb"},"content":{"rendered":"\n<p class=\"has-black-color has-text-color\">&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;<img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"219\" class=\"wp-image-252\" style=\"width: 150px;\" src=\"http:\/\/www.corticalchip.com\/wp-content\/uploads\/2022\/07\/QQ\u56fe\u724720220717104445.jpg\" alt=\"\" srcset=\"https:\/\/www.corticalchip.com\/wp-content\/uploads\/2022\/07\/QQ\u56fe\u724720220717104445.jpg 658w, https:\/\/www.corticalchip.com\/wp-content\/uploads\/2022\/07\/QQ\u56fe\u724720220717104445-206x300.jpg 206w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><br>&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;\u4e2a\u4eba\u90ae\u7bb1\uff1agaohaoran@cqu.edu.cn<\/p>\n\n\n\n<p class=\"has-black-color has-text-color\">&nbsp; &nbsp;&nbsp; &nbsp;\u9ad8\u704f\u7136\uff0c2021\u5e749\u6708\u5165\u5b66\u91cd\u5e86\u5927\u5b66\u5fae\u7535\u5b50\u4e0e\u901a\u4fe1\u5de5\u7a0b\u5b66\u9662\uff0c\u63a8\u8350\u514d\u8bd5\u76f4\u63a5\u653b\u8bfb\u535a\u58eb\u5b66\u4f4d\u3002\u5f53\u524d\u4e3b\u8981\u7814\u7a76\u65b9\u5411\u4e3a\u6df1\u5ea6\u8109\u51b2\u795e\u7ecf\u7f51\u7edc\u53ca\u5927\u6a21\u578b\u7b97\u6cd5\u7814\u7a76\u8bbe\u8ba1\uff0c\u8bfe\u9898\u7ec4\u7c7b\u8111\u6a21\u578b\u7b97\u6cd5\u65b9\u5411\u5b66\u751f\u8d1f\u8d23\u4eba\u3002\u5171\u53d1\u8868\u5b66\u672f\u8bba\u6587 7 \u7bc7\uff0c\u5176\u4e2dSCI 1 \u533a\u4e00\u4f5c 1 \u7bc7\uff0cSCI 2 \u533a\u4e00\u4f5c 1 \u7bc7\uff0c\u516c\u5f00\u53d1\u660e\u4e13\u5229 5 \u9879\u3002\u4e3b\u7814\/\u53c2\u4e0e\u56fd\u5bb6\u91cd\u5927\u7814\u53d1\u8ba1\u5212\u3001\u56fd\u5bb6\u81ea\u7136\u79d1\u5b66\u57fa\u91d1\u91cd\u5927\u7814\u53d1\u8ba1\u5212\u3001\u56fd\u5bb6\u81ea\u7136\u79d1\u5b66\u57fa\u91d1\u91cd\u70b9\u9879\u76ee\u3001\u91cd\u5e86\u5e02\u81ea\u7136\u79d1\u5b66\u57fa\u91d1\u91cd\u70b9\u9879\u76ee\u7b49\uff0c\u4e3b\u6301\u91cd\u5e86\u5e02\u7814\u7a76\u751f\u79d1\u7814\u521b\u65b0\u9879\u76ee\uff0c\u83b7\u5f97\u91cd\u5e86\u5927\u5b66\u4f18\u79c0\u5171\u9752\u56e2\u5458\u3001\u201c\u4e92\u8054\u7f51+\u201d\u5927\u5b66\u751f\u521b\u65b0\u521b\u4e1a\u5927\u8d5b\u91cd\u5e86\u8d5b\u533a\u91d1\u5956\u7b49\u8363\u8a89\u5956\u9879\u3002<\/p>\n\n\n\n<p class=\"has-black-color has-text-color\"><strong>\u7814\u7a76\u65b9\u5411<\/strong><\/p>\n\n\n\n<p class=\"has-black-color has-text-color\">\u6df1\u5ea6\u8109\u51b2\u795e\u7ecf\u7f51\u7edc\u7b97\u6cd5<\/p>\n\n\n\n<p class=\"has-black-color has-text-color\"><strong>\u53d1\u8868\u8bba\u6587<\/strong><\/p>\n\n\n\n<ol class=\"wp-block-list has-black-color has-text-color\">\n<li><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-blue-color\"><a href=\"https:\/\/iopscience.iop.org\/article\/10.1088\/2634-4386\/ae379b\">ATW-SNN: Low-Accuracy-Loss Asymmetric Ternary-Weight Spiking Neural Network with Spike Calibration Strategy<\/a><\/mark><br>\u00a0 \u00a0Yihang Chen, <strong>Haoran Gao,<\/strong> Yingcheng Lin, <strong>Cong Shi*<\/strong>. <em><strong>Neuromorphic Computing and Engineering<\/strong><\/em>, 2026, 6(1). <strong>\uff08SCI\uff0c 1\u533a\uff09<\/strong><br><br><\/li>\n\n\n\n<li><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-blue-color\"><a href=\"https:\/\/iopscience.iop.org\/article\/10.1088\/2634-4386\/ae0a78\" data-type=\"link\" data-id=\"https:\/\/iopscience.iop.org\/article\/10.1088\/2634-4386\/ae0a78\" target=\"_blank\" rel=\"noreferrer noopener\">STOP: Spatiotemporal Orthogonal Propagation for Weight-Threshold-Leakage Synergistic Training of Deep Spiking Neural Networks<\/a><\/mark><br>&nbsp; &nbsp;&nbsp;<strong>Haoran Gao<\/strong>, Xichuan Zhou, Yingcheng Lin, Min Tian, Liyuan Liu, <strong>Cong Shi*<\/strong>. <em><strong>Neuromorphic Computing and Engineering<\/strong><\/em><strong>, <\/strong>2025, 5(4), 1-18. <strong>\uff08SCI\uff0c1\u533a\uff09<\/strong><br><br><\/li>\n\n\n\n<li><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-blue-color\"><a href=\"https:\/\/ieeexplore.ieee.org\/document\/11007130\" data-type=\"link\" data-id=\"https:\/\/ieeexplore.ieee.org\/document\/11007130\" target=\"_blank\" rel=\"noreferrer noopener\">A Visual-Cortex-Mimetic Tiny Neuromorphic Vision Processor Based on Reconfigurable Cortical Neuron Unit<\/a><\/mark><br>&nbsp; &nbsp;&nbsp;Mingju Chen, Junxian He, Haibing Wang, Tengxiao Wang, <strong>Haoran Gao<\/strong>, Liyuan Liu, Ying Wang, Cong Shi*. <em><strong>IEEE Transactions <\/strong><\/em><strong><strong><em>On Circuits and Systems II: Express Briefs<\/em><\/strong><\/strong>,,<strong> <\/strong>2025, 72(7), 943-947.<strong>\uff08SCI\uff0c2\u533a\uff09<\/strong><br><br><\/li>\n\n\n\n<li><mark style=\"background-color:rgba(0, 0, 0, 0);color:#545ff0\" class=\"has-inline-color\"><a href=\"https:\/\/www.mdpi.com\/1424-8220\/23\/24\/9781\">Learnable Leakage and Onset-Spiking Self-Attention in SNNs with Local Error Signals<\/a><\/mark><br>&nbsp; &nbsp; &nbsp;Cong Shi, Li Wang, <strong>Haoran Gao<\/strong>, Min Tian*.  <strong><em>Sensors<\/em><\/strong>: 2023, 23(24), 9781.&nbsp;<strong>\uff08SCI\uff0c3\u533a\uff09<\/strong><br><br><\/li>\n\n\n\n<li><mark style=\"background-color:rgba(0, 0, 0, 0);color:#545ff0\" class=\"has-inline-color\"><a href=\"https:\/\/ieeexplore.ieee.org\/abstract\/document\/10364321\" target=\"_blank\" rel=\"noreferrer noopener\">NORP: A Compact Neuromorphic Olfactory Recognition Processor with On-Chip Hybrid Learning<\/a><\/mark><br>&nbsp; &nbsp; &nbsp;Cong Shi, Yuxuan Wang, Fengchun Tian, Xiang Fu, Haibing Wang, Jingya Zhang, <strong>Haoran Gao<\/strong>, Shukai Duan, Lidan Wang, Min Tian*. <strong><em>IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA)<\/em><\/strong>, 2023, 31-32.<br><br><\/li>\n\n\n\n<li><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-blue-color\"><a href=\"https:\/\/www.frontiersin.org\/articles\/10.3389\/fnins.2023.1141701\/full\" data-type=\"URL\" data-id=\"https:\/\/www.frontiersin.org\/articles\/10.3389\/fnins.2023.1141701\/full\" target=\"_blank\" rel=\"noreferrer noopener\">High-Accuracy Deep ANN-to-SNN Conversion Using Quantization-Aware Training Framework and Calcium-Gated Bipolar Leaky Integrate &amp; Fire Neuron<\/a><\/mark><br>&nbsp; &nbsp; &nbsp;<strong>Haoran Gao<\/strong>, Junxian He, Haibing Wang, Tengxiao Wang, Zhengqing Zhong, Jianyi Yu, Ying Wang, Min Tian, Cong Shi*.&nbsp;<strong><em>Frontiers in Neuroscience<\/em><\/strong>: 2023, 17, 1141701.<strong>\uff08SCI\uff0c2\u533a\uff09<\/strong><br><br><\/li>\n\n\n\n<li><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-blue-color\"><a href=\"https:\/\/ieeexplore.ieee.org\/document\/10024782\" data-type=\"URL\" data-id=\"https:\/\/ieeexplore.ieee.org\/document\/10024782\" target=\"_blank\" rel=\"noreferrer noopener\">An Edge Neuromorphic Hardware with Fast On-Chip Error-Triggered Learning on Compressive Sensed Spikes<\/a><br><\/mark><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-black-color\">&nbsp; &nbsp; &nbsp;Cong Shi, Jingya Zhang, Tengxiao Wang, Zhengqing Zhong, Junxian He, <strong>Haoran Gao<\/strong>, Jianyi Yu, Ping Li, Min Tian*.&nbsp;<strong><em>IEEE Transactions on Circuits and Systems II: Express Briefs<\/em><\/strong>: 2023<\/mark>, 70(7), 2665-2669.<mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-black-color\"><strong>\uff08SCI\uff0c2\u533a\uff09<\/strong><\/mark><br><br><\/li>\n\n\n\n<li><mark style=\"background-color:rgba(0, 0, 0, 0)\" class=\"has-inline-color has-blue-color\"><a href=\"https:\/\/ieeexplore.ieee.org\/document\/9937639\" data-type=\"URL\" data-id=\"https:\/\/ieeexplore.ieee.org\/document\/9937639\" target=\"_blank\" rel=\"noreferrer noopener\">A Lightweight Spiking GAN Model for Memristor-Centric Silicon Circuit with On-Chip Reinforcement Adversarial Learning<\/a><\/mark><br>&nbsp; &nbsp;&nbsp;Min Tian, Jing Lu*, <strong>Haoran Gao<\/strong>, Haibing Wang, Jianyi Yu,&nbsp;Cong Shi.&nbsp;<em><strong>IEEE International Symposium on Circuits &amp; Systems (ISCAS)<\/strong><\/em>: 2022, 3388-3392.<\/li>\n<\/ol>\n\n\n\n<p><\/p>\n\n\n\n<p class=\"has-black-color has-text-color\"><strong>\u53d1\u660e\u4e13\u5229<\/strong><\/p>\n\n\n\n<ol class=\"wp-block-list has-black-color has-text-color\">\n<li>\u4e8b\u4ef6\u9a71\u52a8\u7c7b\u578b\u82af\u7247\u4e2d\u7a81\u89e6\u6743\u91cd\u66f4\u65b0\u65b9\u6cd5\u3001\u82af\u7247\u3001\u7535\u5b50\u8bbe\u5907.<br>\u77f3\u5306*, \u738b\u6d77\u51b0, \u7530\u654f, \u4f55\u4fca\u8d24, \u738b\u817e\u9704, \u55bb\u5251\u4f9d, <strong>\u9ad8\u704f\u7136<\/strong>, \u5f20\u9756\u96c5, \u9648\u4e50\u6bc5, \u9648\u601d\u8c6a, \u5eb9\u4e91\u9e4f. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN116629331A\uff0c2023-08-22<br><br><\/li>\n\n\n\n<li>\u57fa\u4e8eCa-LIF\u795e\u7ecf\u5143\u6a21\u578b\u7684Spike-BP\u7247\u4e0a\u5b66\u4e60\u65b9\u6cd5\u3001\u7cfb\u7edf\u53ca\u5904\u7406\u5668. <br>\u77f3\u5306*, <strong>\u9ad8\u704f\u7136<\/strong>, \u7530\u654f, \u4f55\u4fca\u8d24, \u738b\u817e\u9704, \u55bb\u5251\u4f9d, \u738b\u6d77\u51b0, \u9648\u601d\u8c6a, \u5f20\u9756\u96c5, \u5eb9\u4e91\u9e4f, \u9648\u4e50\u6bc5. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN116629344A\uff0c2023-08-22<br><br><\/li>\n\n\n\n<li>\u57fa\u4e8e\u5168\u8109\u51b2HMAX\u6a21\u578b\u7684\u591a\u5c42\u5377\u79ef\u7c7b\u8111\u82af\u7247. <br>\u77f3\u5306*, \u4f55\u4fca\u8d24, \u738b\u6d77\u51b0, \u738b\u817e\u9704, \u5f20\u9756\u96c5, <strong>\u9ad8\u704f\u7136<\/strong>. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN116562350A\uff0c2023-08-08<br><br><\/li>\n\n\n\n<li>\u4e00\u79cd\u57fa\u4e8e\u6db2\u4f53\u72b6\u6001\u673a\u7684\u8109\u51b2\u795e\u7ecf\u7f51\u7edc\u67b6\u6784.<br>\u77f3\u5306*, \u9648\u4e50\u6bc5, \u7530\u654f, \u4f55\u4fca\u8d24, \u738b\u817e\u9704, \u738b\u6d77\u51b0, \u55bb\u5251\u4f9d, <strong>\u9ad8\u704f\u7136<\/strong>. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN116562354A\uff0c2023-08-08<br><br><\/li>\n\n\n\n<li>\u6df1\u5c42\u8109\u51b2\u795e\u7ecf\u7f51\u7edc\u6a21\u578b\u53ca\u6df1\u5c42SNN\u7247\u4e0a\u5b9e\u65f6\u5b66\u4e60\u5904\u7406\u5668. <br>\u77f3\u5306*\uff0c\u5f20\u9756\u96c5, \u7530\u654f, \u738b\u817e\u9704, \u4f55\u4fca\u8d24, \u55bb\u5251\u4f9d, <strong>\u9ad8\u704f\u7136<\/strong>, \u738b\u6d77\u51b0, \u9648\u4e50\u6bc5, \u9648\u601d\u8c6a, \u5eb9\u4e91\u9e4f. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN116562344A\uff0c2023-08-08<br><br><\/li>\n\n\n\n<li>\u57fa\u4e8e\u53cc\u6a21\u5f0f\u79ef\u5206\u70b9\u706b\u795e\u7ecf\u5143\u7684\u7247\u4e0a\u8109\u51b2\u7f16\u7801\u5668.<br>\u77f3\u5306*, \u5eb9\u4e91\u9e4f, \u949f\u6b63\u9752, \u7530\u654f, \u738b\u6d77\u51b0, \u738b\u817e\u9704, \u4f55\u4fca\u8d24, \u9648\u4e50\u6bc5, \u5f20\u9756\u96c5, \u738b\u4e3d, \u9648\u601d\u8c6a, <strong>\u9ad8\u704f\u7136<\/strong>. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN116050487A\uff0c2023-05-02<br><br><\/li>\n\n\n\n<li>\u8f7b\u91cf\u7ea7\u7247\u4e0a\u5b66\u4e60FPGA\u786c\u4ef6\u67b6\u6784\u53ca\u5176\u8bbe\u8ba1\u65b9\u6cd5.<br>\u77f3\u5306*, \u5f20\u9756\u96c5, \u7530\u654f, \u738b\u817e\u9704, \u738b\u6d77\u51b0, \u4f55\u4fca\u8d24, \u5362\u9756, <strong>\u9ad8\u704f\u7136<\/strong>. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN115115039A\uff0c2022-09-27<br><br><\/li>\n\n\n\n<li>\u4e00\u79cd\u4f4e\u5149\u7167\u5c0f\u50cf\u7d20CFA\u91c7\u6837\u4e0e\u8fb9\u7f18\u8ba1\u7b97\u8bbe\u5907\u9002\u7528\u7684\u53bb\u9a6c\u8d5b\u514b\u65b9\u6cd5.<br>\u77f3\u5306*, \u4efb\u9759, \u674e\u777f, \u738b\u6d77\u51b0, <strong>\u9ad8\u704f\u7136<\/strong>, \u4f55\u4fca\u8d24, \u738b\u817e\u9704, \u738b\u4e3d. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN115082315A\uff0c2022-09-20<br><br><\/li>\n\n\n\n<li>\u57fa\u4e8e\u7b80\u5316SDSP\u7b97\u6cd5\u7684\u8f7b\u91cf\u7ea7\u7247\u4e0a\u5b66\u4e60\u65b9\u6cd5\u3001\u7cfb\u7edf\u53ca\u5904\u7406\u5668.&nbsp;<br>\u9648\u601d\u8c6a, \u77f3\u5306*, \u7530\u654f, \u4f55\u4fca\u8d24, \u738b\u817e\u9704, \u738b\u6d77\u51b0, <strong>\u9ad8\u704f\u7136<\/strong>, \u5eb9\u4e91\u9e4f. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN115018058A\uff0c2022-09-06<br><br><\/li>\n\n\n\n<li>\u57fa\u4e8e\u5fc6\u963b\u5668\u7684\u53ef\u7247\u4e0a\u5f3a\u5316\u5b66\u4e60\u8109\u51b2GAN\u6a21\u578b\u53ca\u8bbe\u8ba1\u65b9\u6cd5.&nbsp;<br>\u77f3\u5306*, \u5362\u9756, \u7530\u654f, \u738b\u6d77\u51b0, \u55bb\u5251\u4f9d, \u4f55\u4fca\u8d24, \u738b\u817e\u9704, <strong>\u9ad8\u704f\u7136<\/strong>. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN114943329A\uff0c2022-08-25<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"<p>&nbsp; &nbsp; &#038; [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-251","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/posts\/251","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"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=251"}],"version-history":[{"count":61,"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/posts\/251\/revisions"}],"predecessor-version":[{"id":2678,"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/posts\/251\/revisions\/2678"}],"wp:attachment":[{"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/media?parent=251"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/categories?post=251"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/tags?post=251"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}