note

Mathematical Understanding and Implementation of Principal Component Analysis (PCA) via Covariance Matrices [Python]

Step 3: Calculation of Eigenvalues and Eigenvectors This is the mathematical highlight of PCA. We perform Eigenvalue Decomposition on the calculated covariance matrix. For the matrix $$ {\Sigma}$$, we ...
GitHub

【保研岛】蓝桥杯Python冲刺课_课时1.py

如 r"this is a line with \n" 则 \n 会显示，并不是换行。 字符串可以用 + 运算符连接在一起，用 * 运算符重复。 Python ...
IEEE

EISPY2D: An Open-Source Python Library for the Development and Comparison of Algorithms in Two-Dimensional Electromagnetic Inverse Scattering Problems

Abstract: Microwave Imaging is a key technique for reconstructing the electrical properties of inaccessible media, relying on algorithms to solve the associated Electromagnetic Inverse Scattering ...
IEEE

A Hardware-Efficient QR Algorithm and Its VLSI Architecture for Eigenvalue Decomposition of Symmetric Matrices

Abstract: This article proposes a novel hardware-efficient QR algorithm and its VLSI architecture to compute the eigenvalue decomposition (EVD) of symmetric matrices. By replacing the computationally ...