Properties that are similar to the memory and learning functions in biological systems have been observed and reported in the experimental studies of memristors fabricated by different materials. These properties incl...Properties that are similar to the memory and learning functions in biological systems have been observed and reported in the experimental studies of memristors fabricated by different materials. These properties include the forgetting effect, the transition from short-term memory（STM） to long-term memory（LTM）, learning-experience behavior, etc. The mathematical model of this kind of memristor would be very important for its theoretical analysis and application design.In our analysis of the existing memristor model with these properties, we find that some behaviors of the model are inconsistent with the reported experimental observations. A phenomenological memristor model is proposed for this kind of memristor. The model design is based on the forgetting effect and STM-to-LTM transition since these behaviors are two typical properties of these memristors. Further analyses of this model show that this model can also be used directly or modified to describe other experimentally observed behaviors. Simulations show that the proposed model can give a better description of the reported memory and learning behaviors of this kind of memristor than the existing model.展开更多
文摘状态迁移矩阵(state transition matrix,简称STM)是一种基于表结构的状态机建模方法,前端为表格形式,后端则具有严格的形式化定义,用于建模软件系统行为.但目前STM不具有时间语义,这极大地限制了该方法在实时嵌入式软件建模方面的应用.针对这一问题,提出了一种基于时间STM(time STM,简称TSTM)的形式化建模方法,通过为STM各单元格增加时间语义和约束,使其适用于实时软件行为刻画.此外,针对TSTM给出了一种基于界限模型检测(bounded model checking,简称BMC)技术的时间计算树逻辑(time computation tree logic,简称TCTL)模型检测方法,以验证TSTM时间及逻辑属性.最后,通过对某型号列控制软件进行TSTM建模与验证,证明了上述方法的有效性.
文摘Properties that are similar to the memory and learning functions in biological systems have been observed and reported in the experimental studies of memristors fabricated by different materials. These properties include the forgetting effect, the transition from short-term memory（STM） to long-term memory（LTM）, learning-experience behavior, etc. The mathematical model of this kind of memristor would be very important for its theoretical analysis and application design.In our analysis of the existing memristor model with these properties, we find that some behaviors of the model are inconsistent with the reported experimental observations. A phenomenological memristor model is proposed for this kind of memristor. The model design is based on the forgetting effect and STM-to-LTM transition since these behaviors are two typical properties of these memristors. Further analyses of this model show that this model can also be used directly or modified to describe other experimentally observed behaviors. Simulations show that the proposed model can give a better description of the reported memory and learning behaviors of this kind of memristor than the existing model.
