摘要
由一名新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-关于机器人的最新研究结果已经发表。根据NewsRx记者在武汉的新闻报道，研究表明：“本文提出了一种仿生定位记忆电路，该电路主要由头部方向单元模块、网格单元模块、放置单元模块和解码模块组成，并将二维连续吸引子网络(CAN)模型模拟为X和Y方向的两个一维模型。”本研究经费来源于国家自然科学基金(NSFC)。新闻记者从华中科技大学的研究中得到一句话：“头部方向单元模块利用记忆器来积分角速度，代表一个人的真实方位，网格单元模块利用记忆器来感知线速度和定向离子信号，这两种信号都是自运动的线索，”该电路接收网格单元模块的输出，在特定的位置触发，解码模块解码单元信息，将神经元状态转换为“一热”码，利用记忆器完成空间定位任务，实现内存计算，摘要:在LTSPICE中实现了上述功能,仿真结果表明,该电路能够实现路径积分和定位,并且具有良好的鲁棒性和较小的抗干扰面积.
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on Robotics have been published. According to news reporting from Wuhan, People's Republic of Ch ina, by NewsRx journalists, research stated, "In this article, a bionic localiza tion memristive circuit is proposed, which mainly consists of head direction cel l module, grid cell module, place cell module and decoding module. This work mod ifies the two-dimensional Continuous Attractor Network (CAN) model of grid cells into two one-dimensional models in X and Y directions." Financial support for this research came from National Natural Science Foundatio n of China (NSFC). The news correspondents obtained a quote from the research from the Huazhong Uni versity of Science and Technology, "The head direction cell module utilizes memr istors to integrate angular velocity and represents the real orientation of an a gent. The grid cell module uses memristors to sense linear velocity and orientat ion signals, which are both self-motion cues, and encodes the position in space by firing in a periodic mode. The place cell module receives the grid cell modul e's output and fires in a specific position. The decoding module decodes the ang le or place information and transfers the neuron state to a 'one-hot' code. This proposed circuit completes the localizing task in space and realizes in-memory computing due to the use of memristors, which can shorten the execution time. Th e functions mentioned above are implemented in LTSPICE. The simulation results s how that the proposed circuit can realize path integration and localization. Mor eover, it is shown that the proposed circuit has good robustness and low area ov erhead."
NETL
NSTL