Spectral Analysis Program (SAP)

Program eliminates or reduces time-consuming aspects of computation of power spectrum for high-frequency communication system. This program was written in FORTRAN IV for UNIVAC 1230 or 1108 computer

Spectral Analysis of Percolation Hamiltonians

We study the family of Hamiltonians which corresponds to the adjacency operators on a percolation graph. We characterise the set of energies which are almost surely eigenvalues with finitely supported eigenfunctions. This set of energies is a dense subset of the algebraic integers. The integrated density of states has discontinuities precisely at this set of energies. We show that the convergence of the integrated densities of states of finite box Hamiltonians to the one on the whole space holds even at the points of discontinuity. For this we use an equicontinuity-from-the-right argument. The same statements hold for the restriction of the Hamiltonian to the infinite cluster. In this case we prove that the integrated density of states can be constructed using local data only. Finally we study some mixed Anderson-Quantum percolation models and establish results in the spirit of Wegner, and Delyon and Souillard.Comment: 19 pages, LaTeX 2e. See also preprint 04-326 on mp_arc. To appear in a slightly different version in "Mathematische Annalen", see the DO

OSSE spectral analysis techniques

Analysis of the spectra from the Oriented Scintillation Spectrometer Experiment (OSSE) is complicated because of the typically low signal to noise (approx. 0.1 percent) and the large background variability. The OSSE instrument was designed to address these difficulties by periodically offset-pointing the detectors from the source to perform background measurements. These background measurements are used to estimate the background during each of the source observations. The resulting background-subtracted spectra can then be accumulated and fitted for spectral lines and/or continua. Data selection based on various environmental parameters can be performed at various stages during the analysis procedure. In order to achieve the instrument's statistical sensitivity, however, it will be necessary for investigators to develop a detailed understanding of the instrument operation, data collection, and the background spectrum and its variability. A brief description of the major steps in the OSSE spectral analysis process is described, including a discussion of the OSSE background spectrum and examples of several observational strategies

Spectral analysis for nonstationary audio

A new approach for the analysis of nonstationary signals is proposed, with a focus on audio applications. Following earlier contributions, nonstationarity is modeled via stationarity-breaking operators acting on Gaussian stationary random signals. The focus is on time warping and amplitude modulation, and an approximate maximum-likelihood approach based on suitable approximations in the wavelet transform domain is developed. This paper provides theoretical analysis of the approximations, and introduces JEFAS, a corresponding estimation algorithm. The latter is tested and validated on synthetic as well as real audio signal.Comment: IEEE/ACM Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, In pres

Data analysis techniques: Spectral processing

The individual steps in the data processing scheme applied to most radars used for wind sounding are analyzed. This processing method uses spectral analysis and assumes a pulse Doppler radar. Improvement in the signal to noise ratio of some radars is discussed

A Polynomial Spectral Calculus for Analysis of DG Spectral Element Methods

We introduce a polynomial spectral calculus that follows from the summation by parts property of the Legendre-Gauss-Lobatto quadrature. We use the calculus to simplify the analysis of two multidimensional discontinuous Galerkin spectral element approximations