A reliable flight tracking control scheme is developed for a fighter in the presence of control surface failures based on adaptive asymmetric Gaussian basis function network (AGBFN).
针对歼击机操纵面结构故障，提出了一种基于自适应不对称高斯基函数网络(agbfn)的可靠跟踪控制方案。
In this paper, the authors study the detection of signals in non-Gaussian noise, and employ a multilayer perceptron neural network as a detector.
本文研究了非高斯噪声中信号的检测，采用多层感知器神经网络作为检测器。
We consider the networked control system (NCS) from linear quadratic Gaussian (LQG) method, switched system and neural network control.
对网络控制系统分别从高斯型二次最优（LQG），切换系统和神经网络控制三个方面来考虑。
The other is neural network control system using Gaussian potential function network(GPFN). The practical operating results illustrate effectiveness and practicability of the proposed system.
另一部分是基于高斯基函数神经网络的控制系统。实际运行结果表明该系统的有效性和实用性。
A linear quadratic Gaussian (LQG) stochastic optimal control was developed for networked control systems with network-induced delays longer than a sampling period using a time-division control mode.
对于网络诱发延迟大于一个采样周期的网络化控制系统，该文研究了该系统的线性二次Gauss (LQG)随机最优控制问题，提出了一种新的分时控制模式。
A linear quadratic Gaussian (LQG) stochastic optimal control was developed for networked control systems with network-induced delays longer than a sampling period using a time-division control mode.
对于网络诱发延迟大于一个采样周期的网络化控制系统，该文研究了该系统的线性二次Gauss (LQG)随机最优控制问题，提出了一种新的分时控制模式。
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