Abstract: The Cellular Neural/Nonlinear Network（CNN） has become a new tool for image and signal processing，robotic and biological visions，and higher brain functions.Robust design for CNN templates is one of the important issues for the practical applications of the CNNs.The purpose is to design a Novel Four Adjoining Points Circle Detection（NFAPCD） CNN and to set up a theorem for robust designs of NFAPCD CNNs.The theorem provides parameter inequalities to determine parameter intervals for implementing prescribed image processing functions.Numerical examples show that theoretical results are effective for computer image processing.

Key words: cellular neural network, 4 adjoining points, robust design

摘要： 细胞神经网络（Cellular Neural Network，CNN）于1988年由L.O.Chua 等人提出，已经成为一种处理图像和视频信号、机器人技术、生物视觉、高级大脑功能的新工具。细胞神经网络模板的鲁棒性设计是CNN在实际应用中碰到的重要课题之一。目的是设计一种能够提取复合4邻域圈的CNN，并对其模板进行鲁棒性设计，给出满足相应功能CNN的鲁棒性定理。该定理提供了能达到预先指定的图像处理功能的CNN模板参数不等式。数值模拟例子说明了理论证明的有效性。

关键词: 细胞神经网络, 4邻域, 鲁棒设计