Designed a control for adopting 3 inputting single output's ADALINE nerve network controller system from here.

由此设计了一个采用3输入单输出的ADALINE神经网络控制的控制系统。

A new design of intelligent fire alert detecting system on multi detector signal fuzzification technic is presented in this paper.

提出一种基于模糊-神经网络的多探息模糊化智能型火灾报警监系统的新方案。

Firstly,the paper utilizes kernel principal component analysis method to realize reduce the dimension of the input vectors and orthogonalize the components of the input vectors.

首先利用核主元分析实现输入变量的降维和去相关,然后用小波神经网络建立预模型。

The ANN starts with simulating cerebric visual thought, and it has wide application foreworld for geological information of underground engineering,taking on strong buzzing, fuzziness, nonlinear.

神经网络方法从模拟人脑的形象思维入手，对于处理具有强噪声、模糊、的地下工程地质息，它具有广阔的应用前景。

In this thesis, PCNN models and its actual application of medical image segmentation are studied.The Pulse Coupled Neuromime (PCN) structure and the mechanism of PCNN are discussed.

本文研究了脉冲耦合神经网络（PCNN）模型及其算法实现，并对其在医学图像分割中的应用做了较为全面的探讨。

In order to further discuss the identification of fault after the detection, a nonlinear online neural network approximator is used to provide an estimate of the fault.

为了进一步实现故障特的辨识与跟踪,讨论了一种利用神经网络对故障模式进行在逼近的鲁棒故障诊断方法。

Designed a control for adopting 3 inputting single output's ADALINE nerve network controller system from here.

由此设计了一个采3输入单输出的ADALINE神经网络控制器的控制系统。

A new design of intelligent fire alert detecting system on multi detector signal fuzzification technic is presented in this paper.

提出一种基于模糊-神经网络的多探测器信息模糊化智能型火灾报警监测系统的新方案。

Firstly,the paper utilizes kernel principal component analysis method to realize reduce the dimension of the input vectors and orthogonalize the components of the input vectors.

首先利核主元分析实现输入变量的降维和去相,神经网络建立预测模型。

The ANN starts with simulating cerebric visual thought, and it has wide application foreworld for geological information of underground engineering,taking on strong buzzing, fuzziness, nonlinear.

神经网络方法从模拟人脑的形象思维入手，对于处理具有强噪声、模糊性、非线性的地下工程地质信息，它具有广阔的应前景。

In this thesis, PCNN models and its actual application of medical image segmentation are studied.The Pulse Coupled Neuromime (PCN) structure and the mechanism of PCNN are discussed.

本文研究了脉冲耦合神经网络（PCNN）模型及其算法实现，并对其在医学图像分割中的应做了较为全面的探讨。

In order to further discuss the identification of fault after the detection, a nonlinear online neural network approximator is used to provide an estimate of the fault.

为了进一步实现故障特性的辨识与跟踪,讨论了一种利神经网络对非线性故障模式进行在线逼近的鲁棒故障诊断方法。

Designed a control for adopting 3 inputting single output's ADALINE nerve network controller system from here.

由此设计了一个采3输入单输出的ADALINE神经网络控制器的控制系统。

A new design of intelligent fire alert detecting system on multi detector signal fuzzification technic is presented in this paper.

提出一种基于糊-神经网络的多探测器信息糊化智能型火灾报警监测系统的新方案。

Firstly,the paper utilizes kernel principal component analysis method to realize reduce the dimension of the input vectors and orthogonalize the components of the input vectors.

首先利元分析实现输入变量的降维和去相关,然后小波神经网络建立预测型。

The ANN starts with simulating cerebric visual thought, and it has wide application foreworld for geological information of underground engineering,taking on strong buzzing, fuzziness, nonlinear.

神经网络方法拟人脑的形象思维入手，对于处理具有强噪声、糊性、非线性的地下工程地质信息，它具有广阔的应前景。

In this thesis, PCNN models and its actual application of medical image segmentation are studied.The Pulse Coupled Neuromime (PCN) structure and the mechanism of PCNN are discussed.

本文研究了脉冲耦合神经网络（PCNN）型及其算法实现，并对其在医学图像分割中的应做了较为全面的探讨。

In order to further discuss the identification of fault after the detection, a nonlinear online neural network approximator is used to provide an estimate of the fault.

为了进一步实现故障特性的辨识与跟踪,讨论了一种利神经网络对非线性故障式进行在线逼近的鲁棒故障诊断方法。

Designed a control for adopting 3 inputting single output's ADALINE nerve network controller system from here.

由此设计了一个采用3输入单输出的ADALINE神经网络控制器的控制系统。

A new design of intelligent fire alert detecting system on multi detector signal fuzzification technic is presented in this paper.

提出一种基于模糊-神经网络的多探测器信息模糊化智能型火灾报警监测系统的新方案。

Firstly,the paper utilizes kernel principal component analysis method to realize reduce the dimension of the input vectors and orthogonalize the components of the input vectors.

首先利用核主元分析实现输入变量的降维和去相关,然后用小波神经网络建立预测模型。

The ANN starts with simulating cerebric visual thought, and it has wide application foreworld for geological information of underground engineering,taking on strong buzzing, fuzziness, nonlinear.

神经网络方法从模拟人脑的形象思维入手，对于处理具有强噪声、模糊性、非线性的地下工程地质信息，它具有广阔的应用前景。

In this thesis, PCNN models and its actual application of medical image segmentation are studied.The Pulse Coupled Neuromime (PCN) structure and the mechanism of PCNN are discussed.

本文研究了脉冲耦合神经网络（PCNN）模型及其算法实现，并对其在像分割中的应用做了较为全面的探讨。

In order to further discuss the identification of fault after the detection, a nonlinear online neural network approximator is used to provide an estimate of the fault.

为了进一步实现故障特性的辨识与跟踪,讨论了一种利用神经网络对非线性故障模式进行在线逼近的鲁棒故障诊断方法。

Designed a control for adopting 3 inputting single output's ADALINE nerve network controller system from here.

由此设计了一个采用3输入单输出的ADALINE神经网络控制器的控制系统。

A new design of intelligent fire alert detecting system on multi detector signal fuzzification technic is presented in this paper.

提出一种基于模糊-神经网络的多探测器信息模糊化智能报警监测系统的新方案。

Firstly,the paper utilizes kernel principal component analysis method to realize reduce the dimension of the input vectors and orthogonalize the components of the input vectors.

首先利用核主元分析实现输入变量的降维和去相关,然后用小波神经网络建立预测模。

The ANN starts with simulating cerebric visual thought, and it has wide application foreworld for geological information of underground engineering,taking on strong buzzing, fuzziness, nonlinear.

神经网络方法从模拟人脑的形象思维入手，对于处有强噪声、模糊性、非线性的地下工程地质信息，它有广阔的应用前景。

In this thesis, PCNN models and its actual application of medical image segmentation are studied.The Pulse Coupled Neuromime (PCN) structure and the mechanism of PCNN are discussed.

本文研究了脉冲耦合神经网络（PCNN）模及其算法实现，并对其在医学图像分割中的应用做了较为全面的探讨。

In order to further discuss the identification of fault after the detection, a nonlinear online neural network approximator is used to provide an estimate of the fault.

为了进一步实现故障特性的辨识与跟踪,讨论了一种利用神经网络对非线性故障模式进行在线逼近的鲁棒故障诊断方法。

Designed a control for adopting 3 inputting single output's ADALINE nerve network controller system from here.

由此设计了一个采用3输入单输出ADALINE网络控制器控制系统。

A new design of intelligent fire alert detecting system on multi detector signal fuzzification technic is presented in this paper.

提出一种基于模糊-网络多探测器信息模糊化智能型火灾报警监测系统新方案。

Firstly,the paper utilizes kernel principal component analysis method to realize reduce the dimension of the input vectors and orthogonalize the components of the input vectors.

首先利用核主元分析实现输入变量降维和去相关,然后用小波网络建立预测模型。

The ANN starts with simulating cerebric visual thought, and it has wide application foreworld for geological information of underground engineering,taking on strong buzzing, fuzziness, nonlinear.

网络方法从模拟人脑形象思维入手，对于处理具有强噪声、模糊性、非线性地下工程地质信息，它具有广阔应用前景。

In this thesis, PCNN models and its actual application of medical image segmentation are studied.The Pulse Coupled Neuromime (PCN) structure and the mechanism of PCNN are discussed.

本文研究了脉网络（PCNN）模型及其算法实现，并对其在医学图像分割中应用做了较为全面探讨。

In order to further discuss the identification of fault after the detection, a nonlinear online neural network approximator is used to provide an estimate of the fault.

为了进一步实现故障特性辨识与跟踪,讨论了一种利用网络对非线性故障模式进行在线逼近鲁棒故障诊断方法。

Designed a control for adopting 3 inputting single output's ADALINE nerve network controller system from here.

由此设计了一个采用3输入单输出的ADALINE神经网络控制器的控制系统。

A new design of intelligent fire alert detecting system on multi detector signal fuzzification technic is presented in this paper.

提出一种基-神经网络的多探测器化智能型火灾报警监测系统的新方案。

Firstly,the paper utilizes kernel principal component analysis method to realize reduce the dimension of the input vectors and orthogonalize the components of the input vectors.

首先利用核主元分析实现输入变量的降维和去相关,然后用小波神经网络建立预测型。

The ANN starts with simulating cerebric visual thought, and it has wide application foreworld for geological information of underground engineering,taking on strong buzzing, fuzziness, nonlinear.

神经网络方法从拟人脑的形象思维入手，对处理具有强噪声、性、非线性的地下工程地质，具有广阔的应用前景。

In this thesis, PCNN models and its actual application of medical image segmentation are studied.The Pulse Coupled Neuromime (PCN) structure and the mechanism of PCNN are discussed.

本文研究了脉冲耦合神经网络（PCNN）型及其算法实现，并对其在医学图像分割中的应用做了较为全面的探讨。

In order to further discuss the identification of fault after the detection, a nonlinear online neural network approximator is used to provide an estimate of the fault.

为了进一步实现故障特性的辨识与跟踪,讨论了一种利用神经网络对非线性故障式进行在线逼近的鲁棒故障诊断方法。

Designed a control for adopting 3 inputting single output's ADALINE nerve network controller system from here.

由此一个采用3输入单输出的ADALINE神经网络控制器的控制系统。

A new design of intelligent fire alert detecting system on multi detector signal fuzzification technic is presented in this paper.

提出一种基于模糊-神经网络的多探测器信息模糊化智能型火灾报警监测系统的新方案。

Firstly,the paper utilizes kernel principal component analysis method to realize reduce the dimension of the input vectors and orthogonalize the components of the input vectors.

首先利用核主元分析输入变量的降维和去相关,然后用小波神经网络建立预测模型。

The ANN starts with simulating cerebric visual thought, and it has wide application foreworld for geological information of underground engineering,taking on strong buzzing, fuzziness, nonlinear.

神经网络方法从模拟人脑的形象思维入手，对于处理具有强噪声、模糊性、非线性的地下工程地质信息，它具有广阔的应用前景。

In this thesis, PCNN models and its actual application of medical image segmentation are studied.The Pulse Coupled Neuromime (PCN) structure and the mechanism of PCNN are discussed.

本文研究脉冲耦合神经网络（PCNN）模型及其算法，并对其在医学图像分割中的应用做较为全面的探讨。

In order to further discuss the identification of fault after the detection, a nonlinear online neural network approximator is used to provide an estimate of the fault.

为进一步故障特性的辨识与跟踪,讨论一种利用神经网络对非线性故障模式进行在线逼近的鲁棒故障诊断方法。

Designed a control for adopting 3 inputting single output's ADALINE nerve network controller system from here.

由此设计了一个采用3输入单输出的ADALINE神经网络控制器的控制系统。

A new design of intelligent fire alert detecting system on multi detector signal fuzzification technic is presented in this paper.

提出一种基模糊-神经网络的多探器信息模糊化智能型火灾报系统的新方案。

Firstly,the paper utilizes kernel principal component analysis method to realize reduce the dimension of the input vectors and orthogonalize the components of the input vectors.

首先利用核主元分析实现输入变量的降维和去相关,然后用小波神经网络建立预模型。

The ANN starts with simulating cerebric visual thought, and it has wide application foreworld for geological information of underground engineering,taking on strong buzzing, fuzziness, nonlinear.

神经网络方法从模拟人脑的形象思维入手，处理具有强噪声、模糊性、非线性的地下工程地质信息，它具有广阔的应用前景。

In this thesis, PCNN models and its actual application of medical image segmentation are studied.The Pulse Coupled Neuromime (PCN) structure and the mechanism of PCNN are discussed.

本文研究了脉冲耦合神经网络（PCNN）模型及其算法实现，并其在医学图像分割中的应用做了较为全面的探讨。

In order to further discuss the identification of fault after the detection, a nonlinear online neural network approximator is used to provide an estimate of the fault.

为了进一步实现故障特性的辨识与跟踪,讨论了一种利用神经网络非线性故障模式进行在线逼近的鲁棒故障诊断方法。