'Spectrum': Spectral Analysis in Python

Spectral mixture analysis of EELS spectrum-images.

Recent advances in detectors and computer science have enabled the acquisition and the processing of multidimensional datasets, in particular in the field of spectral imaging. Benefiting from these new developments, Earth scientists try to recover the reflectance spectra of macroscopic materials (e.g., water, grass, mineral types…) present in an observed scene and to estimate their respective p...

Python Spectral Analysis Tool (pysat) for Preprocessing, Multivariate Analysis, and Machine Learning with Point Spectra

Broadband radio-frequency spectrum analysis in spectral-hole-burning media.

We demonstrate a 20 GHz spectrum analyzer with 1 MHz resolution and >40 dB dynamic range using spectral-hole-burning (SHB) crystals, which are cryogenically cooled crystal hosts lightly doped with rare-earth ions. We modulate a rf signal onto an optical carrier using an electro-optic intensity modulator to produce a signal beam modulated with upper and lower rf sidebands. Illuminating SHB cryst...

Inverse Spectral Analysis : the Case of Discrete Spectrum

We discuss results where the discrete spectrum (or partial information on the discrete spectrum) and partial information on the potential q of a one-dimensional Schrr odinger operator H = ? d 2 dx 2 + q determine the potential completely. Included are theorems for nite intervals and for the whole line. In particular, we pose and solve a new type of inverse spectral problem involving fractions o...

Compositional Performance Analysis in Python with pyCPA

The timing behavior of current and future embedded and distributed systems becomes increasingly complex. At the same time, many application fields such as safety-critical systems require a verification of worst-case timing behavior. Deriving sound guarantees is a complex task, which can be solved by Compositional Performance Analysis. This approach formally computes worst-case timing scenarios ...