# Meeting Details

Title: Application of Hermite expansion in Kalman Filtering method CCMA PDEs and Numerical Methods Seminar Series Yicun Zhen, Math Dept, Penn State University Kalman Filtering is a commonly used method in data assimilation in many scientific areas. In this presentation we will mainly focus on a method of improving the rate of Kalman Filtering. We will not deal with real data today but we will try attacking a localizer matrix which has been used in weather prediction. We will utilize the Hermite expansion to speed up the matrix-vector multiplication process so that conjugate gradient method has the potential to be used to compute $A^{-1}*b$ for matrix $A$ and vector $b$. If the size of the matrix $A$ is n*n, the algorithm for computing the matrix-vector multiplication is hopefully of computational complexity O(n) despite setting up.