Spectra Analysis

This book presents a comprehensive overview of colorimetry and colorimetric analysis of dyes, pigments, paints, pharmaceuticals, and other products via spectrophotometric and spectroscopic analysis.

This book presents a comprehensive overview of colorimetry and colorimetric analysis of dyes, pigments, paints, pharmaceuticals, and other products via spectrophotometric and spectroscopic analysis.

This book presents a comprehensive overview of colorimetry and colorimetric analysis of dyes, pigments, paints, pharmaceuticals, and other products via spectrophotometric and spectroscopic analysis.

This book gives the reader the basic knowledge of the theory of random processes necessary for applying to study climatic time series. It contains many examples in different areas of time series analysis such as autoregressive modelling and spectral analysis, linear extrapolation, simulation, causality, relations between scalar components of multivariate time series, and reconstructions of climate data.

Small-radius tubular structures have attracted considerable attention in the last few years, and are frequently used in different areas such as Mathematical Physics, Spectral Geometry and Global Analysis.

Part of a two volume set based on a recent IMA program of the same name. The goal of the program and these books is to develop a community of statistical and other scientists kept up-to-date on developments in this quickly evolving and interdisciplinary field. Consequently, these books present recent material by distinguished researchers. Topics discussed in Part I include nonlinear and non- Gaussian models and processes (higher order moments and spectra, nonlinear systems, applications in astronomy, geophysics, engineering, and simulation) and the interaction of time series analysis and statistics (information model identification, categorical valued time series, nonparametric and semiparametric methods). Self-similar processes and long-range dependence (time series with long memory, fractals, 1/f noise, stable noise) and time series research common to engineers and economists (modeling of multivariate and possibly non-stationary time series, state space and adaptive methods) are discussed in Part II.