This report discusses the implementation of the shape recovery in case of four harmonics as described in the paper titled Photometric Stereo with General, Unknown Lighting (Basri, Jacobs, Kemelmacher), 2006. The goal is to recover the harmonic images from a set of number of images of an object taken from the same viewpoint but with different illumination. These harmonic images are then used to ...

This note describes a set of routines for the eigenvalue decomposition, singular value decomposition, and Takagi factorization of a complex matrix. Unlike many other implementations, the current ones are all based on the Jacobi algorithm, which makes the code very compact but suitable only for small to medium-sized problems. Although distributed as a library, the routines are self-contained and...

The Lanczos eigensolution takes the dominant amount of time in most normal modes and modal frequency response analyses. This paper introduces a way to reduce the elapsed time of large eigenvalue jobs by using a newly developed parallel option within the Lanczos algorithm. We will compare the performance of the frequency domain decomposition based distributed memory parallel method introduced in...

Multivariate Gaussian models are widely adopted in continuous Estimation of Distribution Algorithms (EDAs), and covariance matrix plays the essential role in guiding the evolution. In this paper, we propose a new framework for Multivariate Gaussian based EDAs (MGEDAs), named Eigen Decomposition EDA (ED-EDA). Unlike classical EDAs, ED-EDA focuses on eigen analysis of the covariance matrix, and i...

Primary User (PU) signal detection is critical for cognitive radio networks as it allows a secondary user to find spectrum holes for opportunistic reuse. Eigenvalue based detection has many advantages, such as it does not require knowledge on primary user signal or noise power level. However, most of the work on eigenvalue based detection methods presented in the literature require multiple sen...