为了契合绿色可再生能源发展理念,自供电环境能量收集系统已逐渐成为替代传统电池的高效解决方案,可克服传统电池在重量、尺寸及循环寿命等方面的局限性。针对压电源的时变特性,设计了一种基于其特性的快速最大功率点跟踪(Maximum Power...为了契合绿色可再生能源发展理念,自供电环境能量收集系统已逐渐成为替代传统电池的高效解决方案,可克服传统电池在重量、尺寸及循环寿命等方面的局限性。针对压电源的时变特性,设计了一种基于其特性的快速最大功率点跟踪(Maximum Power Point Tracking,MPPT)电路架构。对压电源的阻抗特性进行分析,采用了基于快速开关电容采样的开路电压采样MPPT算法,有效实现跟踪精度和动态响应速度的协同优化。最后,基于0.18μm BCD工艺对电路进行设计,仿真结果表明:MPPT的跟踪时间为0.36 ms,最大追踪精度可达99.4%。展开更多
The output voltages for the capacitive elements of a neural circuit model can be mapped into dimensionless capacitive variables,which present firing patterns similar to the membrane potentials detected in biological n...The output voltages for the capacitive elements of a neural circuit model can be mapped into dimensionless capacitive variables,which present firing patterns similar to the membrane potentials detected in biological neurons.The inclusion of a memcapacitor also en‐ables consideration of membrane deformation effects,enhancing the model’s capacity to simulate neuronal behavior across varying physio‐logical and environmental conditions.In this study,a capacitor and a memcapacitor are connected through a linear resistor in parallel with other electric components in different branch circuits composed of an inductor and a nonlinear resistor.The electrical activities in a neuron with a double-layer membrane and two capacitive variables are discussed in detail after converting the nonlinear equations for the neural circuit into a theoretical neuron model.A dimensionless neuron model and its corresponding energy function are derived.The field energy function for the neural circuit is converted into an equivalent Hamilton energy function and further validated via the Helmholtz theorem.Furthermore,the average value of energy serves as an indicator for predicting stochastic resonance,as supported by analyzing the distribu‐tion of the coefficient of variation.The neuronal firing patterns are shown to be energy-dependent.An adaptive control strategy is proposed to regulate mode transitions in electrical activities of the neuron.An analog equivalent circuit is constructed to experimentally verify the nu‐merical results,thereby supporting the reliability of the proposed neuron model.展开更多
文摘为了契合绿色可再生能源发展理念,自供电环境能量收集系统已逐渐成为替代传统电池的高效解决方案,可克服传统电池在重量、尺寸及循环寿命等方面的局限性。针对压电源的时变特性,设计了一种基于其特性的快速最大功率点跟踪(Maximum Power Point Tracking,MPPT)电路架构。对压电源的阻抗特性进行分析,采用了基于快速开关电容采样的开路电压采样MPPT算法,有效实现跟踪精度和动态响应速度的协同优化。最后,基于0.18μm BCD工艺对电路进行设计,仿真结果表明:MPPT的跟踪时间为0.36 ms,最大追踪精度可达99.4%。
基金supported by the National Natural Science Foundation of China(No.12072139).
文摘The output voltages for the capacitive elements of a neural circuit model can be mapped into dimensionless capacitive variables,which present firing patterns similar to the membrane potentials detected in biological neurons.The inclusion of a memcapacitor also en‐ables consideration of membrane deformation effects,enhancing the model’s capacity to simulate neuronal behavior across varying physio‐logical and environmental conditions.In this study,a capacitor and a memcapacitor are connected through a linear resistor in parallel with other electric components in different branch circuits composed of an inductor and a nonlinear resistor.The electrical activities in a neuron with a double-layer membrane and two capacitive variables are discussed in detail after converting the nonlinear equations for the neural circuit into a theoretical neuron model.A dimensionless neuron model and its corresponding energy function are derived.The field energy function for the neural circuit is converted into an equivalent Hamilton energy function and further validated via the Helmholtz theorem.Furthermore,the average value of energy serves as an indicator for predicting stochastic resonance,as supported by analyzing the distribu‐tion of the coefficient of variation.The neuronal firing patterns are shown to be energy-dependent.An adaptive control strategy is proposed to regulate mode transitions in electrical activities of the neuron.An analog equivalent circuit is constructed to experimentally verify the nu‐merical results,thereby supporting the reliability of the proposed neuron model.
