在 数学 和 数值分析里， Ricker 小波

是一种负归二阶高斯函数，也就是能够缩放范式的第二埃尔米特函数。在连续小波的家族当中，埃尔米特小波是个非常特别的存在（应用在连续小波转换称作埃尔米特转换）。Ricker子波经常被采用来仿真地震数据，并作为在计算电动力学的广谱源项。它通常只在美国才会被称作 墨西哥帽小波，是因为在处理内核2D图像时，形成了墨西哥宽边帽的形状。 它也被广为称作 Marr wavelet 因为 David Marr. 这位神经科学家。

而多维一般化的墨西哥帽小波称为高斯函数的拉普拉斯。实际上，这种小波有时会用高斯函的差来逼近，因为它可以被分离，也因此节省大量的计算时间在两维或者更多维的情况。规模标准化拉普拉斯 ( -norm) 经常被用来作为一个blob检测和计算机视觉应用中的自动规模选择。墨西哥帽小波也可以用Cardinal B-Slines 的微分来逼近。

In mathematics and numerical analysis, the Ricker wavelet

is the negative normalized second derivative of a Gaussian function, i.e., up to scale and normalization, the second Hermite function. It is a special case of the family of continuous wavelets (wavelets used in a continuous wavelet transform) known as Hermitian wavelets. The Ricker wavelet is frequently employed to model seismic data, and as a broad spectrum source term in computational electrodynamics. It is usually only referred to as the Mexican hat wavelet in the Americas, due to taking the shape of a sombrero when used as a 2D image processing kernel. It is also known as the Marr wavelet for David Marr.