神经网络系统是一个高度复杂的非线性动力学系统。
The neural networks system is a highly complicated nonlinear kinetics system.
分析了动态递归神经网络系统辨识的参数学习算法。
The parameter learning algorithm of dynamic recurrent neural network based on system identification is analyzed. D.
分析了动态递归神经网络系统辨识的参数学习算法。
The parameter learning algorithm of dynamic recurrent neural network based on system identification is analyzed.
本文提出一种用于联想识别的全光型多值神经网络系统。
In this paper, a design of an all-optical multi-value neural network system for implementation of associative memory is presented.
叙述了粗糙集-神经网络系统诊断电力电子电路的过程。
The diagnosing process of rough set-neural network system is introduced.
人工神经网络系统就像是在仿效人脑工作方式的一种系统。
Artificial Neural Network is a system loosely modeled on the human brain.
对不确定变时滞神经网络系统的鲁棒控制器的设计进行了分析。
Design for robust controller of uncertain neural network with time-varying delay was analyzed.
试验初步证明，所建的神经网络系统的学习和评价效果都令人满意。
The learning and evaluation effects of the artificial neural network in this system are preliminary proved to be satisfactory by tests.
对神经网络系统动力学行为研究的国内外概况和研究方法进行了概括。
A survey is presented on dynamical behavior of neural networks, as well as the methods of research.
MATLAB中的神经网络工具箱是进行神经网络系统分析与设计的有力工具。
MATLAB neural network toolbox is a powerful tool for system analyzing and designing of neural network.
本文针对神经网络系统研究了系统的稳定性问题，给出了更加宽松的稳定条件。
The purpose of this dissertation is to study stability problem and present the more relaxed stability conditions for neural networks with time delays.
本文根据非线性理论，综合考虑各种地质因素并由此建立了一个神经网络系统。
On the basis of nonlinear theory, an artificial neural network system is established in this paper. In the system, many geologic variables are considered comprehensively.
并通过神经网络系统对结构响应进行一步预测，从而进一步提高控制系统的能力。
The ability of the active control system is increased because the response of structure is predicted by the ANN.
把人工免疫系统和神经网络系统的信息处理机制引入到CSA提出了免疫克隆选择算法。
By introducing the information processing mechanism of artificial immune systems and neural network to CSA, an immune clonal selection algorithm (ICSA) was proposed.
本文提出了一个面向股市预测的模糊神经网络系统，并针对系统性能的改善进行了深入研究。
This paper puts forward a fuzzy neural network system aimed at stock price prediction, and an ameliorative method on its function is studied.
由于自适应模糊神经网络系统具有非线性映射和自学习能力，能够用于噪声信号的非线性建模。
The AFNNS has the abilities of nonlinear mapping and self-learning property and can be used to achieve the nonlinear model of the noise.
表明人们在参考生物神经系统来建立人工神经网络系统时必须慎重对待生物神经系统的某些特点。
The work indicates that people should be very careful when they build neural network models by considering the properties of a biological neural system.
这种器件的结构和功能非常类似于人工神经单元模型，所以非常适于在神经电路和神经网络系统中应用。
This function is exactly what is needed for an artificial neuron model to work and the device is no doubt most suitable to construct neural networks.
探讨了神经网络的弱信号检测方法，定性分析了其噪声抑制的原理，给出了神经网络系统框图及实测结果。
This paper inquires into detection method of micro weak signal in neural network, analyses principle of noise suppression, and gives out diagram and measurement results of neural network system.
将人工神经网络技术应用于肥城煤矿区煤层底板突水预报中，并且开发研制成突水预报人工神经网络系统。
Artificial neural network technology is applied to water inrush forecast of coal seam floor of Feicheng mine area.
这样的结果就是大脑里充满了死亡或凋零中的神经细胞，还有无法正常运作的神经网络系统，进而破坏我们的认知能力。
The result is a brain full of dead and dying neurons, and the shutdown of neural connections leads to a drop in cognitive function.
考虑到随机因素及时滞对神经网络系统的稳定性的影响，这使得研究随机时滞神经网络的稳定性具有深远意义。
The impact of stochastic factor and delay on stability of the neural network is significant to investigate the stability of stochastic neural network with delay.
对室内模型试验进行沉降预测，并和实验观测数据以及自适应神经网络系统(ANFIS)预测结果进行了比较。
The subsidence of the indoor model test is also predicted with this theory. The observed data are compared with the predicted data with the adaptive neuro-fuzzy inference system (ANFIS).
从博弈问题的固有属性出发，探讨了解决博弈问题的新途径，并阐述了如何建造解决一类博弈问题的神经网络系统。
From the intrinsic attributes of game problem, a new method of solving game is proposed in this paper. And then the paper describes a neural networks system of one game which we have established.
实验表明，智能神经网络系统原理为克服传统神经网络收敛速度慢的缺点，同时不增加网络负担提供了一种有效方案。
The experiment shows that INNS provides a way to accelerate the astringent speed by constructing a complicate intelligent neural network based on simple networks and by adding some rules.
模糊神经网络系统可以根据系统输入输出信号，建立系统的输入输出关系，并对环境的变化具有较强的自适应学习能力。
Fuzzy Neural Network System (FNNS) can construct input? Output relationship by means of input and output signal and FNNS has special characteristics of adaptive learn while environment is changing.
实验表明，智能神经网络系统组成原理将面向对象、符号逻辑融于神经网络中，提供了构造功能完备的智能系统的途径。
The experiment shows that with merging the Object Oriented concept and symbol logic, the Intelligent Neural Network system Theory provides a way to build a big, complex NN system.
提出了埋设于复合材料内部的光纤系统将成为未来飞行器结构的“神经网络系统”而使结构成为“智能结构”等新概念。
The optical fiber system embedded in composite materials will become a "Neutral Network System" of the future aircraft structures, leading to new concepts of the "Intelligent Structures".
对于用于训练学习的振动信号用小波包变换的方法对信号进行特征值提取得到信号的特征向量，并对神经网络系统进行训练。
The signal eigenvectors of vibration signal for the training were extracted by wavelet packet by the, and then used for neural network training.
对于用于训练学习的振动信号用小波包变换的方法对信号进行特征值提取得到信号的特征向量，并对神经网络系统进行训练。
The signal eigenvectors of vibration signal for the training were extracted by wavelet packet by the, and then used for neural network training.
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