The numerical realization and simulation of the continuous-time stochastic approximation (CSA) identification for stochastic continuous dynamical systems are studied.
本文讨论随机连续动态系统的连续时间随机逼近(CSA)辨识的数值实现及仿真。
The Lagrangian formulation of the critical dynamics is recovered in the second order approximation of fluctuations in the closed time path continuous integral.
在闭路连续积分中取涨落二级近似，得到临界动力学的拉氏场论表述。
For the problem that the input and output of real systems is a continuous process relative to time, this paper proposed a process neural network model for continuous function approximation.
针对实际系统的输入输出是与时间有关的连续过程，提出了一类用于连续过程逼近的过程神经元网络模型。
For the problem that the input and output of real systems is a continuous process relative to time, this paper proposed a process neural network model for continuous function approximation.
针对实际系统的输入输出是与时间有关的连续过程，提出了一类用于连续过程逼近的过程神经元网络模型。
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