用无需选取参数的Unit-linking PCNN进行自动图像分割

脉冲耦合神经网络（PCNN-Pulse Coupled Neural Network）是一种有生物学依据的人工神经网络，它可有效地用于图像分割。基于PCNN的图像分割效果取决于PCNN中各参数的选择。然而，图像分割时，各种不同的图像对应的PCNN参数是不同的，而PCNN参数的选择是困难的。本文提出了一种基于Unit-linking PCNN的图像分割新方法，解决了PCNN图像分割参数选择的难题。用本文提出的新方法可有效地自动分割各种图像，而无需考虑PCNN参数的选择，这对于PCNN的理论研究和实际应用有重要的意义。     

一种基于互相关匹配的简化PCNN及其图像分割

脉冲耦合神经网络(Pulse Coupled Neural Network,PCNN)可有效的用于图像分割,但无法确定最优分割时的迭代次数.针对这一问题,文章从原始图像与分割图像的相似性出发,提出了一种基于最大互相关匹配的简化PCNN图像分割新方法.该算法通过计算原始图像与分割图像的相关匹配系数来确定最优分割.实验结果验证了该方法的有效性.     

基于最大熵和PCNN的图像分割新方法

针对脉冲耦合神经网络(PCNN)无法确定最优分割以及脉冲门限具有非线性因子的问题,提出了一种基于最大熵和脉冲耦合神经网络的新型图像分割算法.该算法采用线性方式动态调整脉冲门限,采用最大熵确定PCNN网络的循环迭代次数,并引用均值滤波的思想对PCNN的接收部分进行了改良,以克服噪声对分割过程的影响.实验结果表明该方法能获得视觉效果较好的分割结果并具有较强的普适性.     

一种基于改进型PCNN的织物疵点图像自适应分割方法

 针对传统脉冲耦合神经网络(Pulse Coupled Neural Network,PCNN)模型中网络参数多、不易自动选取的问题,本文在对PCNN模型进行改进的基础上,提出了一种基于改进型PCNN织物疵点图像自适应分割方法.采用了一种基于分割区域内均匀度差异最小作为最佳迭代次数判断标准,从而有效地满足了PCNN对织物疵点图像的自动分割要求.通过对不同疵点图像分割实验证明了算法对疵点分割的准确性和有效性.     

一种新的基于PCNN的图像自动分割算法研究

脉冲耦合神经网络(PCNN)非常适合图像分割.在参数确定的情况下,分割效果随迭代次数呈周期性变化.因此确定最佳迭代次数是运用PCNN进行图像自动分割的关键.本文提出一种基于连通域计算的边缘统计算法,用于评价迭代结果的有效边缘.最大有效边缘值所对应的迭代输出即为最佳分割.实验证明,该算法比基于图像熵和基于边缘算子的算法灵敏度高,抗噪声能力强.     

一种新的PCNN模型参数估算方法

PCNN在图像处理领域得到广泛的应用,对其展开研究具有重要的理论意义及应用价值.在对PCNN的研究应用中,其模型参数的合理确定是一个难点.本文提出用灰度-信息量直方图来表征图像特征,通过对信息量直方图的分析,提出了估算PCNN时间衰减参数的自适应算法.该算法可以仅在PCNN的一个运行周期中以最少的迭代次数有效地完成图像分割,并且解决了对多目标进行分割时容易丢失目标的问题.     

一种基于简化PCNN的自适应图像分割方法

近年来的研究表明,脉冲耦合神经网络(Pulse Coupled Neural Network,PCNN)可有效地用于图像分割.然而对于不同图像,常需要选取适当的网络参数,以得到有效的分割结果.但是,目前网络参数的选取还主要停留在人工调整和确定阶段,尚无一种能够根据图像本身特性自动确定参数的方法,这在很大程度上限制了PCNN的应用.针对这一问题,本文提出了一种基于简化PCNN的自适应图像分割方法,通过利用图像本身空间和灰度特性自动确定网络参数,实现对不同图像的分割.实验结果表明,本文算法可以有效地对不同图像进行自动分割,具有一定的健壮性.     

基于脉冲耦合神经网络的图像分割方法研究分析

文章研究了基于PCNN模型的图像分割。该方法利用PCNN模型有类似的灰度值与神经元对应可以同时发出脉冲的特征,保留图像的区域信息,显示了更多分割目标的细节信息,文章采用Lena图、Coins图以及经过模糊处理以后的Bike图进行了图像分割,并与最大类间方差Ostu分割方法进行了对比。实验结果表明,脉冲耦合神经网络分割方法利用最小的迭代次数、最快的分割速度,在图像的细节、轮廓以及去模糊方面实现了良好的分割效果。     

基于神经网络的图像分割算法在FPGA上的实现

脉冲耦合神经网络(Pulse Coupled Neural Network,PCNN)是一种新型神经网络模型,作为研究图像分割的常用方法,一直广受关注.针对目前大量文献关注PCNN模型仿真实现研究的情况,本文基于PCNN模型提出了将最小交叉熵分割算法在FPGA硬件平台上进行实现.相比于传统的PCNN软件实现以及最大信息熵分割算法实现的方案,本文提出的图像分割方案最佳分割精准度高,具有处理速度快,实时性强,图像分割效果好的优势,应用范围更广,因此该设计具有较高实际应用价值.     

基于PCNN图像分割新算法

在原有PCNN的基础上提出一种新的参数自适应PCNN模型,该模型中的各参数均由像素点本身决定,而不受人为的外界干涉,因此,该算法在图像处理领域有较好的运用价值。此外提出另一类分割判定准则——最大相关系数判定准则。最后通过对3种不同的图像分割实验结果分析后得出。该算法和最大相关系数判定准则在图像分割领域中具有较强的适应性和较好的辅助意义。     

Technology innovation and process integrations for sub-100nm gate patterning

This paper presents a brief overview of the Applied Centura(R)DPS(R)system,configured with silicon etch DPS Ⅱ chamber, with emphasis on discussing tuning capability for CD uniformity control. It also presents the studies of etch process chemistry and film integration impact for an overall successful gate patterning development. Discussions will focus on resolutions to key issues, such as CD uniformity, line-edge roughness, and multilayer film etching integration.     

White organic light-emitting devices based on fac tris（2- phenylpyridine） iridium sensitized 5,6,11,12-tetraphenylnap -hthacene

We have fabricated the white organic light-emitting devices （WOLEDs） based on 4,4＇ -bis（2,2 -diphenyl vinyl）-1,1＇ - biphenyl （DPVBi） and phosphorescence sensitized 5,6,11,12,-tetraphenylnaphthacene （rubrene）. The device structure is ITO/2T-NATA （20 nm）/NPBX （20 nm）/CBP： x%Ir（ppy）3：0.5% rubrene （8 nm）/NPBX （5 nm）/DPVBi （30 nm）/Alq（30 nm）/LiF（0.5 nm）/A1. In the devices, DPVBi acts as a blue light-emitting layer, the rubrene is sensitized by a phosphorescent material, fac tris （2-phenylpyridine） iridium [Ir（ppy）3], acts as a yellow light-emitting layer, and N,N＇ -bis- （1-naphthyl）- N,N＇ -diphenyl -1, 1＇ -biphenyl-4,4＇ -diamine （NPBX） acts as a hole transporting and exciton blocker layer, respectively. When the concentration of Ir （PPY）3 is 6wt%, the maximum luminance is 24960 cd/m^2 at an applied voltage of 15 V, and the maximum luminous efficiency is 5.17 cd/A at an applied voltage of 8 V.     

Complete approach to automatic identification and subpixel center location for ellipse feature

To meet the need of automatic image features extraction with high precision in visual inspection, a complete approach to automatic identification and sub-pixel center location for similar-ellipse feature is proposed. In the method, the feature area is identified automatically based on the edge attribute, and the sub-pixel center location is accomplished with the leastsquare algorithm. It shows that the method is valid, practical, and has high precision by experiment. Meanwhile this method can meet the need of instrumentation of visual inspection because of easy realization and without man-machine interaction.     

小角度扩展相关性近似算法分析

本论文提出一种在多天线MIMO信道相关性建模中小角度扩展近似理论算法,并应用于分析MIMO系统性能。分析中分别对三种不同角能量分布情况下的空间相关性研发快速近似计算法,并同时提出双模(Bi-Modal)角能量分布情况下的近似运算。通过分析这些新方法的近似效率,可以得到计算简单、复杂度低、而且符合实际的MIMO相关信道矩阵,对系统级的快速高效计算法的研究和系统级的评估以及误差分析具有重要的意义。     

A Versatile Mixed-Signal Pin Approach for Cost-Effective Test of Automotive ICs

Integrated circuits (ICs) intended for increasingly sophisticated automotive applications bring unique test demands. Advanced ICs for applications such as highly integrated automatic braking system (ABS) and airbag controllers combine high voltage digital channels, significant VI demands and precise timing capability. Along with continued missioncritical reliability concerns, the trend toward higher voltage operation and increased device integration requires specialized test capabilities able to extend across the wide operating ranges found in automotive applications. Among these capabilities, automotive test requirements increasingly dictate a need for a cost-effective versatile mixed-signal pin electronics with very high data rates reaching up to 50MHz with a voltage swing of-2 V to +28 V.     

Optical vibration and deviation measurement of rotating machine parts

It is of interest to get appropriate information about the dynamic behaviour of rotating machinery parts in service. This paper presents an approach of optical vibration and deviation measurement of such parts. Essential of this method is an image derotator combined with a high speed camera or a laser doppler vibrometer （LDV）.     

社长序言（英文）

正Happy New Year!As we step into a new year,we take a look back at the key feature topics covered in China Communications over the past 12 months and set out our expecta-     

Call for Papers

正Introduction Jointly sponsored by the China Institute of Communications(CIC)and the IEEE Communications Society(IEEE ComSoc)since the year 2013,China Communications,currently,is aiming to gradually realise the transition from journal to magazine content and style.     

INTEGRATION OF OPTICAL AND WIRELESS NETWORKS

正For a long time,optical and wireless systems/net-works are developed in separate communities witha few attempts for in-depth convergence.In fact,it prom-ises many advantages to combine the optical and wire-less technologies in the levels of systems and networks.Recently,both academia and industry have made manyefforts to enter a new phase of development to take op-tical and wireless systems as fully integrated networks.To provide high bandwidth and reliable service for bothfixed and mobile users,a well-designed network must     

Call for Papers—Feature Topic,Vol.12,No.3,2015

正Smart Grid Communications The electric power industry is undergoing profound changes as the industry aims to capture the promise of a smart grid for a sustainable energy future.Enabled by the advanced sensing devices such as Phasor Measurement Units(PMUs),increasingly powerful