用全局稳定FCHNN在CIELab色彩空间进行图像分割

在张星明等人所做工作的基础上，进一步从李雅普诺夫稳定性原理出发，改进性地设计了具有全局渐进稳定性和全局指数稳定性的模糊竞争Hopfield神经网络（简称GS-FCHNN），用GS-FCHNN进行彩色图像分割，从彩色图像在CIELab空间的色彩分布图获得具有明显色差的色彩值，取该值作为模糊核，从而为神经元建立基于最大隶属度原则的状态函数，实现彩色图像的模糊聚类，达到图像目标分割的目的。实验结果表明：较FCHNN算法，运算时间有明显加快，分割效果不受色彩分布的复杂度的影响，对高斯噪声的自适应能力得到进一步加强。

Using globle stable FCHNN for image segmentation based on CIELab color space

According to the research results of Zhang,an advanced Globle Stable Fuzzy Competitive Hopfield Neural Network is proposed.Using the GS-FCHNN for color image sementation,take the value with obvious color difference in CIELab as fuzzy nuclear,then construct the membership function based on the principle of maximum degree of membership for all neurons,realize image segmentation based on color image fuzzy clustering.The experiment results indicate that the algorithm is better than Zhang,the effect of segmentat...