An Architecture for Solving the Eigenvalue Problem on Embedded FPGAs

Resource-limited embedded devices like Unmanned Aerial Vehicles (UAVs) often rely on offloading or simplified algorithms. Feature extraction such as Principle Component Analysis (PCA) can reduce transmission data without compromising accuracy, or even be used for applications like facial detection. This involves solving eigenvectors and values which is impractical on conventional embedded MCUs.