Stochastic Optimal Control of First Firing Neuron
First-firing statistics of stochastic optimally controlled integrate-and-fire neuron under stimulation of colored noise is investigated. The stochastic averaging principle is utilized and the model equation is approximated by diffusion process and represented by It. stochastic differential equation. The control problems for maximizing the resting probability and maximizing mean first firing time are constructed and the dynamical programming equations associated with the corresponding optimization problem are established. The optimal control law is obtained and the finally controlled It. stochastic differential equation is yielded. The corresponding backward Kolmogorov equation and Pontryagin equation are established and solved to yield the resting probability and mean first firing time. The analytical results are verified by Monte Carlo simulation.
Stochastic Optimal Control Stochastic Averaging First-Spiking Colored Noise Integrate-and-Fire Monte Carlo Simulation
吴勇军 彭建华 罗明
华东理工大学信息科学与工程学院,复杂系统动力学与控制研究室,上海,200237
国内会议
杭州
英文
2008-07-27（万方平台首次上网日期，不代表论文的发表时间）