In studying of a class of random neural network, some of relative researchers have proposed Markov model of neural network.
在一类随机神经网络的研究中，一些研究人员提出马尔科夫神经网络模型。
A novel approach to the real-time speech quality evaluation in a packet network using feed-forward multiple class random neural network (FFMCRNN) was presented.
提出了一种利用前馈随机神经网络在分组网络中进行实时语音质量评价的新方法。
Potentiality of artificial neural network method in copping with a kind of random problem is shown and discussed.
本文指出和讨论了人工神经网络方法在处理某类随机性问题上存在着的潜力。
Use Neural Network to control unfounded model nonlinear random system.
应用神经网络对未建模型的非线性随机系统进行控制。
In this paper, the approaches for recognizing distribution of random data are discussed, and a new approach based on neural network is presented.
本文分析了随机数据分布的识别方法，并提出了基于神经网络的随机数据分布的识别方法。
A fuzzy preprocessing method. that is. fuzzy sliding averaging. is Proposed to decrease the influence of random, an example shows the improvement of the forecasting neural network.
实例结果表明时间序列经模糊滑动平均处理后，随机波动对神经网络预测精度的影响可大大减小。
Because of the fuzzy comprehensive evaluation has subjective and random, we introduce the neural network to improve risk assessment model.
针对模糊综合评判法主观性强，随机性大的缺点，引入模糊神经网络算法对其加以改进。
The neural network model of the equivalent complex refractive of random rain media is developed by means of the improved BP algorithm, based on the electromagnetic wave propagation theory.
利用改进的BP算法，结合电波传播理论，建立了随机雨介质的等效复折射指数的神经网络模型。
Methods: the 32 cases of DSA image data are analysed, the BP Neural Network is used to build diagnostic model, we input 100 cases of random samples to verify the model.
方法：应用BP神经网络模型，分析32例肝癌病例DSA影像资料数据，建立计算机临床辅助诊断模型，然后把100个随机抽样测试样本输入模型验证。
Simulation res ults prove that this new multi-step prediction based on PID-like neural network control system can effectively attenuate random noise interference and is more robust and adaptive.
仿真实验表明，基于多步预测的PID型神经网络控制系统能有效抑制随机干扰，具有较强的适应性和鲁棒性。
Through the test we found that the forecast accuracy of neural network forecasting model is higher than that of random walk model, and there is an obvious difference between two models.
通过检验发现神经网络预测模型在预测精度上要高于随机游动模型，而且两个模型的预测结果存在明显的差异。
A modified BP algorithm of neural network, random adjustment of parameters (RMBP) algorithm, is proposed to overcome the defect of easy going into local minimum of BP neural network.
针对BP(反向传播)神经网络学习易陷入局部极小的缺陷，提出了一种改进BP神经网络学习算法——RMBP算法。
The trend part of the data can be fitted with BP (back propagation) neural network and the random part is processed by a normal ARMA (auto regressive moving average) model.
采用BP网络对不平稳时间序列进行数据拟合，处理趋势部分，利用ARMA模型处理随机部分。
In the chapter 5 the trained fuzzy rule is confirmed by the data adding random noise, the result shows that compensatory fuzzy neural network can respond the trend of theory variety.
在文中的第五章，对补偿模糊神经网络训练的规则用经过噪声污染的数据进行验证，结果表明，网络能比较真实的反应理论结果的变化趋势。
In the chapter 5 the trained fuzzy rule is confirmed by the data adding random noise, the result shows that compensatory fuzzy neural network can respond the trend of theory variety.
在文中的第五章，对补偿模糊神经网络训练的规则用经过噪声污染的数据进行验证，结果表明，网络能比较真实的反应理论结果的变化趋势。
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