43
个编辑
更改
→代表性成果
'''<font color="#ff8000">神经栅格Neurogrid<ref name=":15" /></font>'''是由斯坦福大学Brains in Silicon公司研发的、使用神经形态工程原理设计的硬件。该电路板由16个定制设计的芯片组成(NeuroCores)。在设计中，每个NeuroCore芯片的模拟电路对65536个神经元的神经元素进行模拟，以最大限度地提高能量效率。模拟出的神经元通过设计的数字电路连接，以最大化脉冲吞吐量。<ref name=":16" /><ref name=":17" />
'''<font color="#ff8000">神经栅格Neurogrid<ref name=":15" /></font>'''是由斯坦福大学Brains in Silicon公司研发的、使用神经形态工程原理设计的硬件。该电路板由16个定制设计的芯片组成(NeuroCores)。在设计中，每个NeuroCore芯片的模拟电路对65536个神经元的神经元素进行模拟，以最大限度地提高能量效率。模拟出的神经元通过设计的数字电路连接，以最大化脉冲吞吐量。<ref name=":16" /><ref name=":17" />
A research project with implications for neuromorphic engineering is the [[Human Brain Project]] that is attempting to simulate a complete human brain in a supercomputer using biological data. It is made up of a group of researchers in neuroscience, medicine, and computing.<ref>{{cite web|title=Involved Organizations|url=http://www.humanbrainproject.eu/partners.html|access-date=22 February 2013|url-status=dead|archive-url=https://web.archive.org/web/20130302142627/http://www.humanbrainproject.eu/partners.html|archive-date=2 March 2013}}</ref> [[Henry Markram]], the project's co-director, has stated that the project proposes to establish a foundation to explore and understand the brain and its diseases, and to use that knowledge to build new computing technologies. The three primary goals of the project are to better understand how the pieces of the brain fit and work together, to understand how to objectively diagnose and treat brain diseases, and to use the understanding of the human brain to develop neuromorphic computers. That the simulation of a complete human brain will require a supercomputer a thousand times more powerful than today's encourages the current focus on neuromorphic computers.<ref>{{cite web|title=Human Brain Project|url=http://www.humanbrainproject.eu|access-date=22 February 2013}}</ref> $1.3 billion has been allocated to the project by The [[European Commission]].<ref>{{cite web|title=The Human Brain Project and Recruiting More Cyberwarriors|url=http://www.marketplace.org/topics/tech/human-brain-project-and-recruiting-more-cyberwarriors|access-date=22 February 2013|date=January 29, 2013}}</ref>
A research project with implications for neuromorphic engineering is the [[Human Brain Project]] that is attempting to simulate a complete human brain in a supercomputer using biological data. It is made up of a group of researchers in neuroscience, medicine, and computing.<ref name=":18">{{cite web|title=Involved Organizations|url=http://www.humanbrainproject.eu/partners.html|access-date=22 February 2013|url-status=dead|archive-url=https://web.archive.org/web/20130302142627/http://www.humanbrainproject.eu/partners.html|archive-date=2 March 2013}}</ref> [[Henry Markram]], the project's co-director, has stated that the project proposes to establish a foundation to explore and understand the brain and its diseases, and to use that knowledge to build new computing technologies. The three primary goals of the project are to better understand how the pieces of the brain fit and work together, to understand how to objectively diagnose and treat brain diseases, and to use the understanding of the human brain to develop neuromorphic computers. That the simulation of a complete human brain will require a supercomputer a thousand times more powerful than today's encourages the current focus on neuromorphic computers.<ref name=":19">{{cite web|title=Human Brain Project|url=http://www.humanbrainproject.eu|access-date=22 February 2013}}</ref> $1.3 billion has been allocated to the project by The [[European Commission]].<ref name=":20">{{cite web|title=The Human Brain Project and Recruiting More Cyberwarriors|url=http://www.marketplace.org/topics/tech/human-brain-project-and-recruiting-more-cyberwarriors|access-date=22 February 2013|date=January 29, 2013}}</ref>
'''<font color="#ff8000">人类大脑计划Human Brain Project</font>'''对神经形态工程具有较大影响，其主要任务是尝试用生物数据在超级计算机中模拟完整的人脑。人类大脑计划由神经科学、医学和计算机科学背景的研究人员组成。<ref name=":18" />该项目的联合主管亨利•马克拉姆(Henry Markram)表示，人类大脑计划的目的是建立一个探索和了解脑科学和脑疾病知识的基础，并利用这些知识来构建更先进的计算机技术。这个项目的三个主要目标分别是: 更好地理解大脑的各个部分是如何相互配合协同工作的; 理解如何客观地诊断和治疗脑部疾病; 以及利用对人类大脑的理解来开发神经形态计算机。模拟一个完整的人类大脑需要一台比现在强大一千倍的超级计算机，这不断激发着对神经形态计算机领域的研究兴趣。<ref name=":19" />欧盟委员会已经向人类大脑计划拨款13亿美元。<ref name=":20" />
Other research with implications for neuromorphic engineering involves the [[BRAIN Initiative]]<ref name="economist">[https://www.economist.com/news/science-and-technology/21582495-computers-will-help-people-understand-brains-better-and-understanding-brains Neuromorphic computing: The machine of a new soul], The Economist, 2013-08-03</ref> and the [[TrueNorth]] chip from [[IBM]].<ref name=":21">{{cite journal|last1=Modha|first1=Dharmendra|title=A million spiking-neuron integrated circuit with a scalable communication network and interface|journal=Science|date=Aug 2014|volume=345|issue=6197|pages=668–673|doi=10.1126/science.1254642|pmid=25104385|bibcode=2014Sci...345..668M|s2cid=12706847}}</ref> Neuromorphic devices have also been demonstrated using nanocrystals, nanowires, and conducting polymers.<ref name=":22">{{Cite web|url=http://jessamynfairfield.com/wp-content/uploads/2017/03/PWMar17Fairfield.pdf|title=Smarter Machines|last=Fairfield|first=Jessamyn|date=March 1, 2017}}</ref>
其他与神经形态工程有关的研究还包括'''<font color="#ff8000">脑计划BRAIN initiative</font>'''，<ref name="economist" />和IBM研发的'''<font color="#ff8000">TrueNorth</font>'''芯片。<ref name=":21" />使用纳米晶体、纳米线和导电聚合物也能够用于制造神经形态学硬件。<ref name=":22" />
[[Intel]] unveiled its neuromorphic research chip, called “[[Intel Loihi|Loihi]]”, in October 2017. The chip uses an asynchronous [[spiking neural network]] (SNN) to implement adaptive self-modifying event-driven fine-grained parallel computations used to implement learning and inference with high efficiency.<ref name=":23">{{cite journal |last1=Davies |first1=Mike |title=Loihi: A Neuromorphic Manycore Processor with On-Chip Learning |journal=IEEE Micro |date=January 16, 2018 |volume=38 |issue=1 |pages=82–99 |display-authors=etal|doi=10.1109/MM.2018.112130359 |s2cid=3608458 }}</ref><ref name="Morris2017">{{cite web |last1=Morris |first1=John |title=Why Intel built a neuromorphic chip |url=https://www.zdnet.com/article/why-intel-built-a-neuromorphic-chip/ |website=ZDNet |access-date=17 August 2018 |language=en}}</ref>
2017年10月，英特尔发布了神经形态芯片'''<font color="#ff8000">Loihi</font>'''。该芯片采用异步'''<font color="#ff8000">脉冲神经网络Spiking neural network</font>'''实现了自适应、自修改、事件驱动的细粒度并行计算，实现了高效的学习和推理。<ref name=":23" /><ref name="Morris2017" />
[[Intel]] unveiled its neuromorphic research chip, called “[[Intel Loihi|Loihi]]”, in October 2017. The chip uses an asynchronous [[spiking neural network]] (SNN) to implement adaptive self-modifying event-driven fine-grained parallel computations used to implement learning and inference with high efficiency.<ref>{{cite journal |last1=Davies |first1=Mike |title=Loihi: A Neuromorphic Manycore Processor with On-Chip Learning |journal=IEEE Micro |date=January 16, 2018 |volume=38 |issue=1 |pages=82–99 |display-authors=etal|doi=10.1109/MM.2018.112130359 |s2cid=3608458 }}</ref><ref name="Morris2017">{{cite web |last1=Morris |first1=John |title=Why Intel built a neuromorphic chip |url=https://www.zdnet.com/article/why-intel-built-a-neuromorphic-chip/ |website=ZDNet |access-date=17 August 2018 |language=en}}</ref>
[[IMEC]], a Belgium-based nanoelectronics research center, demonstrated the world's first self-learning neuromorphic chip. The brain-inspired chip, based on OxRAM technology, has the capability of self-learning and has been demonstrated to have the ability to compose music.<ref name=":24">{{cite web |title=Imec demonstrates self-learning neuromorphic chip that composes music |url=https://www.imec-int.com/en/articles/imec-demonstrates-self-learning-neuromorphic-chip-that-composes-music |website=IMEC International |access-date=1 October 2019}}</ref> IMEC released the 30-second tune composed by the prototype. The chip was sequentially loaded with songs in the same time signature and style. The songs were old Belgian and French flute minuets, from which the chip learned the rules at play and then applied them.<ref name=":25">{{cite web|last1=Bourzac|first1=Katherine|title=A Neuromorphic Chip That Makes Music|url=https://spectrum.ieee.org/a-neuromorphic-chip-that-makes-music|url-status=live|access-date=1 October 2019|website=IEEE Spectrum|date=May 23, 2017}}</ref>
比利时的'''<font color="#ff8000">微电子研究中心IMEC</font>'''研发了世界上首个自学习神经形态芯片。这种基于'''<font color="#32CD32"> OxRAM(filamentary-oxide-based resistive memory technology)</font>''' 技术的大脑启发芯片具有自学习能力，并且已被证明具有创作音乐的能力。<ref name=":24" />IMEC发布了由芯片原型机谱写的30秒旋律。向芯片加载一系列特征、风格统一的歌曲（古代比利时和法国长笛小步舞曲），芯片从中学习相关规则并将其应用于创作。<ref name=":25" />
[[Blue Brain Project|The Blue Brain Project]], led by Henry Markram, aims to build biologically detailed digital reconstructions and simulations of the mouse brain. The Blue Brain Project has created in silico models of rodent brains, while attempting to replicate as many details about its biology as possible. The supercomputer-based simulations offer new perspectives on understanding the structure and functions of the brain.
[[Blue Brain Project|The Blue Brain Project]], led by Henry Markram, aims to build biologically detailed digital reconstructions and simulations of the mouse brain. The Blue Brain Project has created in silico models of rodent brains, while attempting to replicate as many details about its biology as possible. The supercomputer-based simulations offer new perspectives on understanding the structure and functions of the brain.
由亨利·马克拉姆领导的'''<font color="#ff8000">蓝脑计划The Blue Brain Project</font>'''旨在建立小鼠大脑生理学细节的数字重建和模拟。蓝脑计划已经建立了啮齿动物大脑的电子模型，同时进行着尽可能多地复制其生理学细节的尝试。基于超级计算机的模拟为理解大脑的结构和功能提供了新的视角。
The European Union funded a series of projects at the University of Heidelberg, which led to the development of
The European Union funded a series of projects at the University of Heidelberg, which led to the development of
BrainScaleS (brain-inspired multiscale computation in neuromorphic hybrid systems), a hybrid analog neuromorphic supercomputer located at Heidelberg University, Germany. It was developed as part of the Human Brain Project neuromorphic computing platform and is the complement to the SpiNNaker supercomputer (which is based on digital technology). The architecture used in BrainScaleS mimics biological neurons and their connections on a physical level; additionally, since the components are made of silicon, these model neurons operate on average 864 times (24 hours of real time is 100 seconds in the machine simulation) that of their biological counterparts.
[[BrainScaleS]] (brain-inspired multiscale computation in neuromorphic hybrid systems), a hybrid analog [[neuromorphic]] supercomputer located at Heidelberg University, Germany. It was developed as part of the [[Human Brain Project]] neuromorphic computing platform and is the complement to the [[SpiNNaker]] supercomputer (which is based on digital technology). The architecture used in BrainScaleS mimics biological neurons and their connections on a physical level; additionally, since the components are made of silicon, these model neurons operate on average 864 times (24 hours of real time is 100 seconds in the machine simulation) that of their biological counterparts.<ref name=":26">{{Cite web|date=2016-03-21|title=Beyond von Neumann, Neuromorphic Computing Steadily Advances|url=https://www.hpcwire.com/2016/03/21/lacking-breakthrough-neuromorphic-computing-steadily-advance/|access-date=2021-10-08|website=HPCwire|language=en-US}}</ref>
欧盟资助了海德堡大学一系列促进BrainScaleS(神经形态混合系统中受大脑启发的多尺度计算)发展的项目，这是一台位于德国海德堡大学的混合模拟'''<font color="#ff8000">神经形态Neuromorphic</font>'''超级计算机。它是作为人类大脑计划中神经形态计算平台的一部分而开发的，是'''<font color="#ff8000">SpiNNaker</font>'''超级计算机(基于数字技术)的补充。BrainScaleS中使用的体系架构模拟了生物神经元及其在物理层面上的连接；此外，由于这些组件是由硅制成的，这些模型神经元平均运行速度是生物神经元的864倍，这意味着在机器模拟中，24小时的实时时间仅为100秒。<ref name=":26" />
===Neuromorphic sensors ===
===Neuromorphic sensors===
===神经形态传感器===
===神经形态传感器===
The concept of neuromorphic systems can be extended to sensors (not just to computation). An example of this applied to detecting [[light]] is the [[retinomorphic sensor]] or, when employed in an array, the [[event camera]].
The concept of neuromorphic systems can be extended to sensors (not just to computation). An example of this applied to detecting [[light]] is the [[retinomorphic sensor]] or, when employed in an array, the [[event camera]].
神经形态系统的概念可以扩展到传感器(而不仅仅是计算单元)。一个用于检测光线的例子是'''<font color="#ff8000">类视网膜传感器Retinomorphic sensor</font>'''，或者'''<font color="#ff8000">事件摄像机Event camera</font>阵列。'''
==Ethical considerations==
==Ethical considerations ==
==伦理问题==
==伦理问题==
While the interdisciplinary concept of neuromorphic engineering is relatively new, many of the same ethical considerations apply to neuromorphic systems as apply to [[human-like machines]] and [[artificial intelligence]] in general. However, the fact that neuromorphic systems are designed to mimic a [[human brain]] gives rise to unique ethical questions surrounding their usage.
While the interdisciplinary concept of neuromorphic engineering is relatively new, many of the same ethical considerations apply to neuromorphic systems as apply to [[human-like machines]] and [[artificial intelligence]] in general. However, the fact that neuromorphic systems are designed to mimic a [[human brain]] gives rise to unique ethical questions surrounding their usage.
然而，实际上的争论是，神经形态硬件和人工“神经网络”是大脑如何运作或处理信息的极其简化的模型，在大小和功能技术方面的复杂性要低得多，在连接方面的结构则更加规则。将神经形态芯片与大脑进行比较是一种非常粗糙的比较，类似于仅仅因为一架飞机有翅膀和一条尾巴就将它与一只鸟进行比较。事实上，神经认知系统比当前最先进的人工智能具有更多的能量和计算效率，而神经形态工程是一种通过从大脑机制中激发灵感来缩小这种差距的尝试，就像许多工程设计具有生物启发的特征一样。数量级。
然而，实际上的争论是，神经形态硬件和人工“神经网络”是大脑如何运作或处理信息的极其简化的模型，在大小和功能技术方面的复杂性要低得多，在连接方面的结构则更加规则。将神经形态芯片与大脑进行比较是一种非常粗糙的比较，类似于仅仅因为一架飞机有翅膀和一条尾巴就将它与一只鸟进行比较。事实上，神经认知系统比当前最先进的人工智能具有更多的能量和计算效率，而神经形态工程是一种通过从大脑机制中激发灵感来缩小这种差距的尝试，就像许多工程设计具有生物启发的特征一样。数量级。
===Democratic concerns ===
===Democratic concerns===
===公众担忧===
===公众担忧 ===
Significant ethical limitations may be placed on neuromorphic engineering due to public perception.<ref>{{Cite report|url=https://ai100.stanford.edu/sites/g/files/sbiybj9861/f/ai_100_report_0831fnl.pdf|title=Artificial Intelligence and Life in 2030|author=2015 Study Panel|date=September 2016|work=One Hundred Year Study on Artificial Intelligence (AI100)|publisher=Stanford University}}</ref> Special [[Eurobarometer]] 382: Public Attitudes Towards Robots, a survey conducted by the European Commission, found that 60% of [[European Union]] citizens wanted a ban of robots in the care of children, the elderly, or the disabled. Furthermore, 34% were in favor of a ban on robots in education, 27% in healthcare, and 20% in leisure. The European Commission classifies these areas as notably “human.” The report cites increased public concern with robots that are able to mimic or replicate human functions. Neuromorphic engineering, by definition, is designed to replicate the function of the human brain.<ref name=":1">{{Cite web|url=http://ec.europa.eu/commfrontoffice/publicopinion/archives/ebs/ebs_382_en.pdf|title=Special Eurobarometer 382: Public Attitudes Towards Robots|last=European Commission|date=September 2012|website=European Commission}}</ref>
Significant ethical limitations may be placed on neuromorphic engineering due to public perception.<ref>{{Cite report|url=https://ai100.stanford.edu/sites/g/files/sbiybj9861/f/ai_100_report_0831fnl.pdf|title=Artificial Intelligence and Life in 2030|author=2015 Study Panel|date=September 2016|work=One Hundred Year Study on Artificial Intelligence (AI100)|publisher=Stanford University}}</ref> Special [[Eurobarometer]] 382: Public Attitudes Towards Robots, a survey conducted by the European Commission, found that 60% of [[European Union]] citizens wanted a ban of robots in the care of children, the elderly, or the disabled. Furthermore, 34% were in favor of a ban on robots in education, 27% in healthcare, and 20% in leisure. The European Commission classifies these areas as notably “human.” The report cites increased public concern with robots that are able to mimic or replicate human functions. Neuromorphic engineering, by definition, is designed to replicate the function of the human brain.<ref name=":1">{{Cite web|url=http://ec.europa.eu/commfrontoffice/publicopinion/archives/ebs/ebs_382_en.pdf|title=Special Eurobarometer 382: Public Attitudes Towards Robots|last=European Commission|date=September 2012|website=European Commission}}</ref>
围绕神经形态工程的民主关注可能在未来变得更加深刻。欧盟委员会(European Commission)发现，15至24岁的欧盟公民比55岁以上的欧盟公民更有可能认为机器人像人(而不是像仪器)。当看到一张被定义为“类人”的机器人图片时，年龄在15岁至24岁之间的欧盟公民中有75% 的人表示，这与他们对机器人的想法相符，而55岁以上的欧盟公民中只有57% 的人有同样的反应。因此，类似人类的神经形态系统，可以把它们归入许多欧盟公民希望在未来禁止使用的机器人类别。
围绕神经形态工程的民主关注可能在未来变得更加深刻。欧盟委员会(European Commission)发现，15至24岁的欧盟公民比55岁以上的欧盟公民更有可能认为机器人像人(而不是像仪器)。当看到一张被定义为“类人”的机器人图片时，年龄在15岁至24岁之间的欧盟公民中有75% 的人表示，这与他们对机器人的想法相符，而55岁以上的欧盟公民中只有57% 的人有同样的反应。因此，类似人类的神经形态系统，可以把它们归入许多欧盟公民希望在未来禁止使用的机器人类别。
===Personhood===
=== Personhood===
=== 人格问题===
===人格问题===
As neuromorphic systems have become increasingly advanced, some scholars{{who|date=August 2021}} have advocated for granting [[personhood]] rights to these systems. If the brain is what grants humans their personhood, to what extent does a neuromorphic system have to mimic the human brain to be granted personhood rights? Critics of technology development in the [[Human Brain Project]], which aims to advance brain-inspired computing, have argued that advancement in neuromorphic computing could lead to machine consciousness or personhood.<ref>{{Cite journal|last=Aicardi|first=Christine|date=September 2018|title=Accompanying technology development in the Human Brain Project: From foresight to ethics management|journal=Futures|volume=102|pages=114–124|doi=10.1016/j.futures.2018.01.005|doi-access=free}}</ref> If these systems are to be treated as people, critics argue, then many tasks humans perform using neuromorphic systems, including the act of termination of neuromorphic systems, may be morally impermissible as these acts would violate the autonomy of the neuromorphic systems.<ref>{{Cite journal|last=Lim|first=Daniel|date=2014-06-01|title=Brain simulation and personhood: a concern with the Human Brain Project|journal=Ethics and Information Technology|language=en|volume=16|issue=2|pages=77–89|doi=10.1007/s10676-013-9330-5|s2cid=17415814|issn=1572-8439}}</ref>
As neuromorphic systems have become increasingly advanced, some scholars{{who|date=August 2021}} have advocated for granting [[personhood]] rights to these systems. If the brain is what grants humans their personhood, to what extent does a neuromorphic system have to mimic the human brain to be granted personhood rights? Critics of technology development in the [[Human Brain Project]], which aims to advance brain-inspired computing, have argued that advancement in neuromorphic computing could lead to machine consciousness or personhood.<ref>{{Cite journal|last=Aicardi|first=Christine|date=September 2018|title=Accompanying technology development in the Human Brain Project: From foresight to ethics management|journal=Futures|volume=102|pages=114–124|doi=10.1016/j.futures.2018.01.005|doi-access=free}}</ref> If these systems are to be treated as people, critics argue, then many tasks humans perform using neuromorphic systems, including the act of termination of neuromorphic systems, may be morally impermissible as these acts would violate the autonomy of the neuromorphic systems.<ref>{{Cite journal|last=Lim|first=Daniel|date=2014-06-01|title=Brain simulation and personhood: a concern with the Human Brain Project|journal=Ethics and Information Technology|language=en|volume=16|issue=2|pages=77–89|doi=10.1007/s10676-013-9330-5|s2cid=17415814|issn=1572-8439}}</ref>
<nowiki>作为物理记忆网络和外部源的性质的函数。在上述方程中，α 是“遗忘”时间尺度常数，xi = r-1，r = frac { r _ text { off }{ on }{ r _ text { on }}是记忆电阻器极限电阻的开关和开关值之比，vec s 是电路源的矢量，Omega 是电路基本环路的投影仪。常数 β 具有电压的尺寸，与记忆电阻器的特性有关; 它的物理起源是导体中的电荷迁移率。对角矩阵和向量 w = 操作者名{ diag }(vec w)和 vec w 分别是记忆电阻器的内值，值在0到1之间。因此，这个等式需要在内存值上添加额外的约束，以保证可靠性。</nowiki>
<nowiki>作为物理记忆网络和外部源的性质的函数。在上述方程中，α 是“遗忘”时间尺度常数，xi = r-1，r = frac { r _ text { off }{ on }{ r _ text { on }}是记忆电阻器极限电阻的开关和开关值之比，vec s 是电路源的矢量，Omega 是电路基本环路的投影仪。常数 β 具有电压的尺寸，与记忆电阻器的特性有关; 它的物理起源是导体中的电荷迁移率。对角矩阵和向量 w = 操作者名{ diag }(vec w)和 vec w 分别是记忆电阻器的内值，值在0到1之间。因此，这个等式需要在内存值上添加额外的约束，以保证可靠性。</nowiki>
==See also==
== See also==
== 相关词条 ==
== 相关词条==
{{Columns-list|colwidth=18em|
{{Columns-list|colwidth=18em|
* [[AI accelerator (computer hardware)|AI accelerator]]
* [[AI accelerator (computer hardware)|AI accelerator]]
{{Portal bar|Electronics}}
{{Portal bar|Electronics}}
==References==
== References==
{{Reflist|40em}}
{{Reflist|40em}}
==External links==
== External links==
<!--======================== {{No more links}} ============================
<!--======================== {{No more links}} ============================
| PLEASE BE CAUTIOUS IN ADDING MORE LINKS TO THIS ARTICLE. Wikipedia |
| PLEASE BE CAUTIOUS IN ADDING MORE LINKS TO THIS ARTICLE. Wikipedia |
*Telluride Neuromorphic Engineering Workshop
*Telluride Neuromorphic Engineering Workshop
*CapoCaccia Cognitive Neuromorphic Engineering Workshop
*CapoCaccia Cognitive Neuromorphic Engineering Workshop
* Institute of Neuromorphic Engineering
*Institute of Neuromorphic Engineering
*INE news site.
*INE news site.
*Frontiers in Neuromorphic Engineering Journal
*Frontiers in Neuromorphic Engineering Journal
*碲化物神经形态工程工作室
*碲化物神经形态工程工作室
*CapoCaccia 认知神经形态工程工作室
*CapoCaccia 认知神经形态工程工作室
*神经形态工程研究所
* 神经形态工程研究所
*INE 新闻站点。
*INE 新闻站点。
*《神经形态工程学前沿》
*《神经形态工程学前沿》