Spectral data estimation from image data is an ill-posed problem since (i) due to the integral nature of solid-state light sensors the same output can be obtained from an infinity...
We introduce a novel method of test generation for microprocessors at the RTL using spectral methods. Test vectors are generated for RTL faults, which are the stuck-at faults on i...
Abstract— This paper presents a novel use of spectral clustering algorithms to support cases where the entries in the affinity matrix are costly to compute. The method is increm...
Christoffer Valgren, Tom Duckett, Achim J. Lilient...
We propose a spectral partitioning approach for large-scale optimization problems, specifically structure from motion. In structure from motion, partitioning methods reduce the pr...
Recently, a number of researchers have proposed spectral algorithms for learning models of dynamical systems—for example, Hidden Markov Models (HMMs), Partially Observable Marko...