{"id":232,"date":"2022-07-17T00:21:05","date_gmt":"2022-07-16T16:21:05","guid":{"rendered":"https:\/\/www.corticalchip.com\/?p=232"},"modified":"2026-10-13T02:15:45","modified_gmt":"2026-10-12T18:15:45","slug":"%e5%96%bb%e5%89%91%e4%be%9d%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\/%e5%96%bb%e5%89%91%e4%be%9d%e4%b8%aa%e4%ba%ba%e7%ae%80%e4%bb%8b\/","title":{"rendered":"\u55bb\u5251\u4f9d\u4e2a\u4eba\u7b80\u4ecb"},"content":{"rendered":"\n

 \"\"
\u4e2a\u4eba\u90ae\u7bb1\uff1ajianyiyu@cqu.edu.cn<\/p>\n\n\n\n

\u55bb\u5251\u4f9d\uff0c2020\u5e746\u6708\u672c\u79d1\u6bd5\u4e1a\u4e0e\u91cd\u5e86\u5927\u5b66\u5fae\u7535\u5b50\u4e0e\u901a\u4fe1\u5de5\u7a0b\u5b66\u9662\uff0c\u5e76\u4e8e2020\u5e749\u6708\u63a8\u514d\u81f3\u8be5\u5b66\u9662\u76f4\u63a5\u653b\u8bfb\u535a\u58eb\u7814\u7a76\u751f\u30022022\u5e747-8\u6708\u8d74\u676d\u5dde\u6d77\u5eb7\u5a01\u89c6\u516c\u53f8\u5b9e\u4e60\uff0c\u53c2\u4e0e\u5148\u8fdb\u82af\u7247\u8bbe\u8ba1\u30022022\u5e749\u6708-2024\u5e7412\u6708\u8d74\u6e05\u534e\u5927\u5b66\u7535\u5b50\u5de5\u7a0b\u7cfb\u667a\u80fd\u611f\u77e5\u96c6\u6210\u7535\u8def\u4e0e\u7cfb\u7edf\u5b9e\u9a8c\u5ba4\uff0c\u8fdb\u884c\u8054\u5408\u57f9\u517b\u3002\u73b0\u62c5\u4efb\u8bfe\u9898\u7ec4\u5b58\u5185\u8ba1\u7b97\u7c7b\u8111\u82af\u7247\u65b9\u5411\u5b66\u751f\u5c0f\u7ec4\u8d1f\u8d23\u4eba\uff0c<\/strong>\u7814\u7a76\u65b9\u5411\u4e3a\u57fa\u4e8e\u6570\u5b57\u5b58\u5185\u8ba1\u7b97\u6280\u672f\u7684\u8109\u51b2\u795e\u7ecf\u7f51\u7edc\u63a8\u7406\u8bad\u7ec3\u4e00\u4f53\u5316\u7c7b\u8111\u5904\u7406\u5668\u8bbe\u8ba1\u3002\u5171\u53c2\u4e0e4\u9879\u56fd\u5bb6\u548c\u7701\u90e8\u7ea7\u79d1\u7814\u8bfe\u9898\uff0c1\u9879\u6d77\u5eb7\u5a01\u89c6\u6570\u5b57\u6280\u672f\u80a1\u4efd\u6709\u9650\u516c\u53f8\u5148\u5bfc\u9879\u76ee\uff0c\u5df2\u53d1\u8868\u5b66\u672f\u8bba\u658712\u7bc7\uff0c\u516c\u5f00\u53d1\u660e\u4e13\u52297\u9879\uff0c\u83b7\u5f972025\u5e74\u7b2c\u516b\u5c4a\u4e2d\u56fd\u7814\u7a76\u751f\u521b\u201c\u82af\u201d\u5927\u8d5b\u56e2\u961f\u4f18\u79c0\u5956\u3002<\/p>\n\n\n\n

\u53d1\u8868\u8bba\u6587<\/strong><\/p>\n\n\n\n

    \n
  1. A 65-nm Precision-Reconfigurable Neuromorphic Digital Compute-In-Memory Macro with Aligned Storage for Synaptic Weights and Membrane Potentials<\/mark>
    Jianyi Yu, <\/strong>Yuxuan Wang, Yu Pan, Yufei Liu, Fei Qiao, Ying Wang, Rui Yuan,<\/em> Liyuan Liu, Cong Shi*. Neuromorphic Computing and Engineering<\/strong><\/em>, 2026, accepted. \uff08SCI, <\/strong>1\u533a\uff09<\/strong>
    <\/li>\n\n\n\n
  2. A Digital SRAM-Based Compute-In-Memory Macro for Weight-Stationary Dynamic Matrix Multiplication in Transformer Attention Score Computation<\/a><\/mark><\/mark>
    Jianyi Yu<\/strong>, Tengxiao Wang, Yuxuan Wang, Xiang Fu, Fei Qiao, Ying Wang, Rui Yuan, Liyuan Liu, Cong Shi*. Microelectronics Journal<\/em><\/strong>, 2026, 177. \uff08SCI, 2\u533a\uff09<\/strong>
    <\/li>\n\n\n\n
  3. A Precision-Reconfigurable eDRAM-Based Neuromorphic Compute-In-Memory Macro With Aligned Storage and Selective Refresh<\/mark>
    Jianyi Yu, <\/strong>Yufei Liu, Yu Pan, Cong Shi*. International Conference on Frontiers Technology in Circuits and Systems (FTCS), <\/em><\/strong>2026, accepted.
    <\/li>\n\n\n\n
  4. AM-CIM: Approximate Memory Based Near Sensor Compute-in-Memory Architecture for Keyword Spotting<\/a><\/mark>
    Yuhao Liu, Xiaotao Jia*, Guangcai Yuan, Jianyi Yu<\/strong>, <\/strong>Cong Shi, Qi Wei, Youguang Zhang, Weisheng Zhao, Fei Qiao*.IEEE Transactions on Circuits and Systems I: Regular Papers<\/strong><\/em>, 2025, doi: 10.1109\/TCSI.2025.3580398.\uff08SCI\uff0c1\u533a\uff09<\/strong>
    <\/li>\n\n\n\n
  5. \u4e00\u79cd\u57fa\u4e8e\u6a21\u62df\u57df\u7279\u5f81\u63d0\u53d6\u7684\u8bed\u97f3\u6d3b\u52a8\u68c0\u6d4b\u7535\u8def<\/a>
    \u4f55\u5efa\u5e73\uff0c\u6768\u5175\uff0c\u5f20\u9759\uff0c\u4e54\u98de\uff0c\u8d3e\u51ef\u6b4c\uff0c\u9b4f\u7426\uff0c\u5218\u7389\u6d69\uff0c\u55bb\u5251\u4f9d<\/strong>\uff0c\u77f3\u5306.\u7269\u8054\u7f51\u6280\u672f<\/em> <\/strong>. 2025 ,15 (05),16-20.
    <\/li>\n\n\n\n
  6. An 8-T Processing-in-Memory SRAM Cell-Based Pixel-Parallel Array Processor for Vision Chips<\/a><\/mark>
    Leyi Chen, Cong Shi, Junxian He, Jianyi Yu<\/strong>, Haibing Wang, Jing Lu, Liyuan Liu, Nanjian Wu, Min Tian*. IEEE Transactions on Circuits and Systems I: Regular Papers<\/em><\/strong>: 2023, 70(11), 4249-4259.\uff08SCI\uff0c1\u533a\uff09<\/strong>
    <\/li>\n\n\n\n
  7. High-Accuracy Deep ANN-to-SNN Conversion Using Quantization-Aware Training Framework and Calcium-Gated Bipolar Leaky Integrate & Fire Neuron<\/a><\/mark>
    Haoran Gao, Junxian He, Haibing Wang, Tengxiao Wang, Zhengqing Zhong, Jianyi Yu<\/strong>, Ying Wang, Min Tian, Cong Shi*. Frontiers in Neuroscience<\/em><\/strong>: 2023, 17, 1141701.\uff08SCI\uff0c2\u533a\uff09<\/strong>
    <\/li>\n\n\n\n
  8. An Edge Neuromorphic Hardware with Fast On-Chip Error-Triggered Learning on Compressive Sensed Spikes<\/a>
    <\/mark>Cong Shi, Jingya Zhang, Tengxiao Wang, Zhengqing Zhong, Junxian He, Haoran Gao, Jianyi Yu<\/strong>, Ping Li, Min Tian*. IEEE Transactions on Circuits and Systems II: Express Briefs<\/em><\/strong>: 2023<\/mark>, 70(7), 2665-2669.\uff08SCI\uff0c2\u533a\uff09<\/strong><\/mark>
    <\/li>\n\n\n\n
  9. An 8-T Processing-in-Memory SRAM Cell-Based <\/mark>Pixel-Parallel Array Processor for Vision Chips<\/a><\/mark>
    Leyi Chen, Junxian He, Jianyi Yu<\/strong>, Haibing Wang, Jing Lu, Liyuan Liu, Nanjian Wu, Cong Shi, Min Tian*. IEEE Asia Pacific Conference on Circuits and Systems<\/strong><\/em> (APCCAS)<\/em><\/strong>: 2022, 1-5.(Best Paper Award)<\/strong>
    <\/li>\n\n\n\n
  10. TEDOP: a Tiny Event-Driven Neural Network Hardware Core Enabling On-Chip Spike-Driven Synaptic Plasticity<\/a><\/mark>
    Cong Shi, Sihao Chen, Haibing Wang, Zhengqing Zhong, Ping Li, Junxian He, Tengxiao Wang, Jianyi Yu<\/strong>, Min Tian*. IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA)<\/em><\/strong>: 2022, pp. 62-63.
    <\/li>\n\n\n\n
  11. A Lightweight Spiking GAN Model for Memristor-Centric Silicon Circuit with On-Chip Reinforcement Adversarial Learning<\/a><\/mark>
    Min Tian, Jing Lu*, Haoran Gao, Haibing Wang, Jianyi Yu<\/strong>, Cong Shi. IEEE International Symposium on Circuits & Systems (ISCAS)<\/strong><\/em>: 2022, 3388-3392.
    <\/li>\n\n\n\n
  12. A Heterogeneous Spiking Neural Network for Computationally Efficient Face Recognition<\/a>
    Xichuan Zhou, Zhenghua Zhou, Zhengqing Zhong, Jianyi Yu<\/strong>, Tengxiao Wang, Min Tian, Ying Jiang, Cong Shi*. IEEE International Symposium on Circuits & Systems (ISCAS)<\/strong><\/em>: 2021, 1-5<\/li>\n<\/ol>\n\n\n\n

    <\/p>\n\n\n\n

    \u53d1\u660e\u4e13\u5229<\/strong><\/p>\n\n\n\n

      \n
    1. \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.
      \u77f3\u5306*, \u738b\u6d77\u51b0, \u7530\u654f, \u4f55\u4fca\u8d24, \u738b\u817e\u9704, \u55bb\u5251\u4f9d<\/strong>, \u9ad8\u704f\u7136, \u5f20\u9756\u96c5, \u9648\u4e50\u6bc5, \u9648\u601d\u8c6a, \u5eb9\u4e91\u9e4f. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN116629331A\uff0c2023-08-22
      <\/li>\n\n\n\n
    2. \u57fa\u4e8eCa-LIF\u795e\u7ecf\u5143\u6a21\u578b\u7684Spike-BP\u7247\u4e0a\u5b66\u4e60\u65b9\u6cd5\u3001\u7cfb\u7edf\u53ca\u5904\u7406\u5668.
      \u77f3\u5306*, \u9ad8\u704f\u7136, \u7530\u654f, \u4f55\u4fca\u8d24, \u738b\u817e\u9704, \u55bb\u5251\u4f9d<\/strong>, \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
      <\/li>\n\n\n\n
    3. \u4e00\u79cd\u57fa\u4e8e\u6db2\u4f53\u72b6\u6001\u673a\u7684\u8109\u51b2\u795e\u7ecf\u7f51\u7edc\u67b6\u6784.
      \u77f3\u5306*, \u9648\u4e50\u6bc5, \u7530\u654f, \u4f55\u4fca\u8d24, \u738b\u817e\u9704, \u738b\u6d77\u51b0, \u55bb\u5251\u4f9d<\/strong>, \u9ad8\u704f\u7136. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN116562354A\uff0c2023-08-08
      <\/li>\n\n\n\n
    4. \u6df1\u5c42\u8109\u51b2\u795e\u7ecf\u7f51\u7edc\u6a21\u578b\u53ca\u6df1\u5c42SNN\u7247\u4e0a\u5b9e\u65f6\u5b66\u4e60\u5904\u7406\u5668.
      \u77f3\u5306*\uff0c\u5f20\u9756\u96c5, \u7530\u654f, \u738b\u817e\u9704, \u4f55\u4fca\u8d24, \u55bb\u5251\u4f9d<\/strong>, \u9ad8\u704f\u7136, \u738b\u6d77\u51b0, \u9648\u4e50\u6bc5, \u9648\u601d\u8c6a, \u5eb9\u4e91\u9e4f. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN116562344A\uff0c2023-08-08
      <\/li>\n\n\n\n
    5. \u5b58\u5185\u8ba1\u7b97\u88c5\u7f6e\u53ca\u5176\u63a7\u5236\u65b9\u6cd5.
      \u77f3\u5306*, \u9648\u4e50\u6bc5, \u7530\u654f, \u738b\u6d77\u51b0, \u55bb\u5251\u4f9d<\/strong>, \u4f55\u4fca\u8d24. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN115064197A\uff0c2022-09-16
      <\/li>\n\n\n\n
    6. \u57fa\u4e8e\u5fc6\u963b\u5668\u7684\u53ef\u7247\u4e0a\u5f3a\u5316\u5b66\u4e60\u8109\u51b2GAN\u6a21\u578b\u53ca\u8bbe\u8ba1\u65b9\u6cd5. 
      \u77f3\u5306*, \u5362\u9756, \u7530\u654f, \u738b\u6d77\u51b0, \u55bb\u5251\u4f9d<\/strong>, \u4f55\u4fca\u8d24, \u738b\u817e\u9704, \u9ad8\u704f\u7136. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN114943329A\uff0c2022-08-25
      <\/li>\n\n\n\n
    7. \u57fa\u4e8e\u8109\u51b2\u795e\u7ecf\u7f51\u7edc\u7684\u5b9e\u65f6\u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5\u3001\u7cfb\u7edf\u53ca\u5904\u7406\u5668.
      \u738b\u817e\u9704, \u77f3\u5306*, \u7530\u654f, \u4f55\u4fca\u8d24, \u738b\u6d77\u51b0, \u55bb\u5251\u4f9d<\/strong>. \u4e2d\u56fd\uff0c\u516c\u5f00\u53f7\uff1aCN114065922A\uff0c2022-02-18<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

       \u4e2a\u4eba\u90ae\u7bb1\uff1ajian […]<\/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-232","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/posts\/232","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=232"}],"version-history":[{"count":77,"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/posts\/232\/revisions"}],"predecessor-version":[{"id":3590,"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/posts\/232\/revisions\/3590"}],"wp:attachment":[{"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/media?parent=232"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/categories?post=232"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.corticalchip.com\/index.php\/wp-json\/wp\/v2\/tags?post=232"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}