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This article presents a anomaly detection method based on correlation eigen matrix and neural network.

本文描述了一个基于相关特征矩阵和神经网络的异常检测方法。

Through learning the part of experimental data by BP algorithm, a multi-layer artificial neural network was established and integrated with the counterflow condenser model.

通过对部分实验数据的学习,进一步建立了与基本模型相结合的人工神经网络

But the ODOG based on the vision selective attention mechanism can effectively collect the interesting information and then segment the image by the coupled oscillation of the PCNN.

而基于视觉选择注意机制的方向性高斯差算子通过模拟生物视觉感受野的特点,在有效提取感兴趣区域的信息后,再通过脉冲耦合神经网络模型的自适应振荡,可达到图像分割的目的。

Present the improving model named SAMPCNN by combing the PCNN and ODOG. The traditional PCNN model, if only by its characteristic of coupled oscillation, is not ideally in image segmentation.

传统脉冲耦合神经网络模型在应用于图像分割时,若仅仅依靠模型的同步振荡特性,效果并不理想。

In order to solve the problem how to construct covariance matrix that used prescient information of measurement data in least-square-method,a cellular localization algorithm based on the BP neural network is proposed.

为了解决最小二乘法需要测量数据的先验信息来构造协方差矩阵的问题,提出了基于BP神经网络的蜂窝无线定位算法。

In order to solve the problem how to construct covariance matrix that used prescient information of measurement data in least-square-method, a cellular location algorithm based on the RBF neural network is proposed.

为了解决最小二乘法需要测量数据的先验信息来构造协方差矩阵的问题,提出了基于RBF神经网络的蜂窝无线定位算法。

Depending on getting the crossway transportation data, the intention of the study is to make use of the expert system, neural network and genetic algorithm to analyze the dynamic characteristic of transportation and to form the global optimization control order, and to realize the local signal lamp control by the method of utilization fuzzy control.

研究的目标是在交通数据采集的基础上利用专家系统、神经网络、遗传算法等技术分析交通动态特征、形成全局优化调度指令,并利用模糊控制的方法实现交叉口的信号灯控制。

Crudely put, the brain's neural networks can be thought of as electrical circuits.

粗俗点说,人大脑的神经网络就如同一个电子回路。

And the next is the principles and construction methods of cryptographic schemes based on neural networks.

论文着重研究了数字地球神经系统的模型和应用,以及基于神经网络的密码算法的原理和构造。

As both are disciplines researching information processing, neural network will be applied in cryptology widely.

作为同是研究信息处理的两门学科,神经网络在密码学中有着广泛而重要的应用前景。

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