在学习过程中通过同时调整小波基函数的平移因子和隶属度函数的形状，使得模糊小波网络的精度和泛化能力大大提高。
By adjusting the translation parameters of the wavelets and the shape of membership functions, the accuracy and generalization capability of FWN can be remarkably improved.
为解决此问题，提出一种基于捕食-被捕食的粒子群优化模糊聚类算法且聚类中心采用密度函数初始化。
To solve the problem, a fuzzy clustering based on predator prey PSO algorithm is presented, which is using density function to initialize cluster centre.
算法重点考虑到成像过程中必然引入的各种噪声，用高斯分布函数模糊化直线参数，使提取具有良好的稳健性。
The new method puts emphases on dealing with all kinds of noise from the imaging process, and USES Gaussian distribution to blur parameters of straight lines in order to ensure extraction robustness.
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