The model and properties of PCNN was analyzed.
根据PCNN神经元是否点火，来获取织物疵点信息；
The PCNN implementation and applications in image processing were discussed.
讨论了PCNN的实现方法及其在图像处理中的应用等问题。
By using the auto wave character of PCNN, this method can locate the seal in the image.
利用PCNN的自动波的特性，可有效的定位印文在图像中的位置。
The research shows that the pulse transmission feature of PCNN is able to perform different image processing.
研究发现，可用PCNN的脉冲传播特性有效地解决图像处理中的不同问题。
Thus, we not only reveal the inherent ability of PCNN, but also explore the applications of PCNN in pattern recognition.
这些算法不仅是对PCNN潜质的深度挖掘，同时也是对PCNN在模式识别应用中的有益探索。
PCNN model has similar group neurons synchronization release pulse characteristic, appropriate for the image segmentation.
PCNN模型具有相似群神经元同步发放脉冲的特性，适合于图像分割。
This paper first brings forward a new approach for binary image thinning by using the pulse transmission attribute of PCNN.
该文首次提出了如何用PCNN的脉冲传播特性进行二值图像细化的新方法。
This paper brings forward a new approach for region labeling by using double Pulse Coupled Neural Networks (PCNN) and morphology.
提出了一种双层脉冲耦合神经网络与数学形态学相结合的区域标识算法。
An algorithm for medical X-ray image enhancement based on human visual properties and improved PCNN image factorization is proposed.
提出一种基于人眼视觉特性和改进的PCNN图像因子分解的X线医学图像增强算法。
Given only an input and the desired output, the adaptive PCNN system can find all parameter values necessary to approximate the desired output.
该系统对于给定的期望输出和实际输入，能够自动调节参数数值使实际输出接近期望输出。
The algorithm that segments images with pulse-coupled neural networks(PCNN) and two-dimension maximum correlation criterion(MCC) was presented.
提出了一种脉冲耦合神经网络和最大相关准则相结合的算法来对图像进行分割。
Although the PCNN algorithms dealing with different problems of image processing are not same, they all use the pulse transmission attribute of...
虽然解决图像处理中的不同问题时，基于PCNN的算法有所不同，但有一共同点，就是都用到了PCNN的脉冲传播特性。
Although the PCNN algorithms dealing with different problems of image processing are not same, they all use the pulse transmission attribute of PCNN.
虽然解决图像处理中的不同问题时，基于PCNN的算法有所不同，但有一共同点，就是都用到了PCNN的脉冲传播特性。
This paper introduces a new method of low contrast gray image enhancement based on PCNN after studying the operation elements and action mechanism of PCNN.
通过对PCNN工作原理和行为机制的深刻剖析，本文提出基于PCNN的低对比度的灰度图像增强算法。
These images are firstly segmented by PCNN and labeled, and then morphologically processed to extract the approximate locations and contours of polysaccharides.
使用PCNN二值分割后图像经过标记、特征参数提取和形态学处理初步获得图像中多糖分子位置和初始轮廓。
Simulation results demonstrate the effectiveness of the proposed method, and the chaotic PCNN systems can be controlled from chaotic state to stable expectation.
仿真和实验结果证明了该算法的有效性，实现了混沌pcnn系统从混沌状态到稳定期望点的控制。
In the text the Max entropy and the Max cross entropy are respectively selected as the image segmentation criterions and the PCNN model has been rationally simplified.
分别选择最大熵和最大交叉熵作为PCNN图像分割准则，并对PCNN模型进行合理简化。
The experimental results show that GIT-PCNN is better than classical PCNN-based segmentation algorithms on visual evaluation, subjective indices and speed performance.
实验结果表明，GIT -PCNN在主观及客观的分割性能和速度上均优于经典的PCNN分割方法。
In this paper, a new method of low contrast image enhancement is presented based on PCNN and LR models in conjunction with characteristics of human visual consciousness.
针对低对比度图像，结合人眼视觉神经系统的感知特性，提出了一种基于PCNN与LR模型的图像增强方法。
Through the experiment, the PCNN method is efficient, it can segment seal texture from the whole seal image precisely and PCA method can also register the seals precisely.
通过试验表明，本文提出的结合PCNN的方法可准确的将有效印文从复杂背景中分割出来。
The entropy series and neurons firing series of the image obtained by feeding the spectrogram into PCNN were used as the characteristics of emotion speech for emotion recognition.
该方法将语音转化为语谱图后输入到PCNN，得到输出图像的神经元点火序列及其熵序列作为语音情感的特征，利用其特征实现语音情感识别。
This paper research on SAR de-noises and target recognition with PCNN. Results were reached in this paper about adoption of PCNN in the de-noise and recognition of SAR image through tests.
本文主要研究PCNN在SAR降噪和目标特征提取过程中的应用，通过对比PCNN方法和现有方法的实验效果确定PCNN在SAR目标识别过程的适用性。
Concerning the fusion problem of multi-focus image with the same scene, an algorithm of image fusion based on wavelet transform and adaptive Pulse Coupled Neural Network (PCNN) was proposed.
针对同一场景多聚焦图像的融合问题，提出了一种基于小波变换的自适应脉冲耦合神经网络(PCNN)图像融合方法。
Using the invariable characteristics of PCNN time series and entropy series of Spectrogram, people can extract the feature of speakers speech and recognize the speakers rapidly and effectively.
该方法将语谱图输入到PCNN后得到输出图像的时间序列及其熵序列作为说话人语音的特征，利用它的不变性实现说话人识别。
When segmenting a image using PCNN, the inner pixel and the pixel on edge in same area have different linking input due to amount of adjacent activating pixel, this causes improper segmentation.
传统PCNN应用于图像分割时，同属于一个区域的内部像素和边缘像素，由于其相邻的被激活像素的个数不同造成连接输入明显不同，这往往造成了误分割。
A method of detecting the textile defects by using Pulsed Coupled Neural Network (PCNN) is proposed according to the difference of gray intensity between normal fabric images and textile defects.
根据织物表面图像的灰度强度和织物疵点图像的灰度强度的不同，运用PCNN对织物疵点进行自动检测。
It presents principal component analysis on image based on neighborhood unions of per-pixel to obtain the eigenvector of per-pixel, then USES PCNN to set on fire to segment image with feature image.
通过对图像在每个像素的邻域的基础上进行主分量分析，产生每个图像像素的特征向量，再用PCNN对得到的特征图像进行点火分割。
Then the experimental results show that the vector median filtering algorithm based on PCNN and HIS not only can effectively remove the noise, but also can protect the details of color image better.
通过分析彩色图像的数据格式，将八叉树量化方法用于彩色图像的颜色信息量化，并采用矢量中值滤波消除彩色图像噪声，以实现对彩色图像的合理预处理。
For the specific implementation of PCNNs, a PCNN was forced to be a single pass network. And simplified model, look-up threshold table, and integer operation were used to decrease the time complexity.
在PCNN的具体实现中，网络被强制为单循环网络，通过简化模型、阈值查找表、整数运算等技巧，降低了PCNN的时间复杂度。
For the specific implementation of PCNNs, a PCNN was forced to be a single pass network. And simplified model, look-up threshold table, and integer operation were used to decrease the time complexity.
在PCNN的具体实现中，网络被强制为单循环网络，通过简化模型、阈值查找表、整数运算等技巧，降低了PCNN的时间复杂度。
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