脑—机接口系统是一个不依靠外周神经和肌肉组织等而实现大脑和外界装置之间直接的交流和控制的通道。
Brain-computer interface (BCI) systems support direct communication and control between brain and external devices without any use of peripheral nerves and muscles.
刺激控制装置可包括一范围内的低和高强度刺激，以刺激并评估神经和肌肉两者。
A stimulation control device may incorporate a range of low and high intensity stimulation to provide a stimulation and evaluation of both nerves and muscles.
刺激大脑深处神经群的植入装置有助于控制癫痫和帕金森氏病。
Implants that stimulate nerve clusters deep within the brain can help control epilepsy and Parkinson's disease.
仿真结果表明，神经网络、自适应逆控制方法可以成功地解决装置中现有的控制问题，并取得良好的效果。
The results of simulation show that the existing control problem of the plant can be successfully solved by neural network, adaptive inverse control and the result is good.
提出基于自适应网络模糊推理系统(ANFIS)的神经模糊控制器作为船舶减摇鳍系统的控制装置。
In this paper, we present an Adaptive Network-based fuzzy Inference system (ANFIS), based on a neuro-fuzzy controller, as a possible control mechanism for a ship stabilizing fin system.
提出基于自适应网络模糊推理系统(ANFIS)的神经模糊控制器作为船舶减摇鳍系统的控制装置。
In this paper, we present an Adaptive Network-based fuzzy Inference system (ANFIS), based on a neuro-fuzzy controller, as a possible control mechanism for a ship stabilizing fin system.
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