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An unabridged and corrected republication of Part I and Part II of The measurement of power spectra from the point of view of communications engineering, which originally appeared in the January 1958 and March 1958 issues of volume XXXVII of the Bell system technical journal.
The use of standard techniques for measuring the power spectra of stationary phenomena in the treatment of nonstationary physical phenomena can lead to erroneous results. Some of the tools available for the analysis of nonstationary random phenomena are outlined in this report and the applicability of these tools to some practical engineering problems is discussed.
This report discusses the general problem of recording and analyses of wave, submarine, and fluid motion data obtained from the USS Redfin while hovering at keel depths (near 100 feet) at different relative headings. In particular, the problem of recording surface wave heights with the Sonic Surface Scanner is discussed. Power spectral estimates obtained by both analog and digital methods are presented. Composite graphs of power spectra of data are presented, and mean values of the motion are given in tabulated form.
Skill-scores, relative to climatology, for some parameters such as ceiling/visibility and precipitation are much lower than others, such as minimum temperature and pressure gradients. Also, the skill-scores have been improving appreciably faster for forecasts of 36 h (and more) than for forecasts of 24 h (and less). At the shortest ranges, less than 12 h, skill-scores relative to persistence are rather low, with values of 0.0 to 0.5 as typical. Power spectra for wind, temperature, dew point, rainfall rate, cloud reflectivity, and extinction coefficient (inversely related to visibility) were computed for periods of 10 min to 20 days, using fall season data from northeast United States. Analys...
Computing time dependent power spectra is an important method for studying nonstationarities in signals. An efficient procedure for computing such spectra and displaying them immediately is requisite for effective application. The method presented is based on a date window which moves along the signal in unit increments. The spectrum is updated for each new sample. All spectra are displayed on a computer graphic terminal and the algorithm was deliberately constructed to make computer graphic display efficient. (Author).
This book provides a thorough introduction to methods for detecting and describing cyclic patterns in time-series data. It is written both for researchers and students new to the area and for those who have already collected time-series data but wish to learn new ways of understanding and presenting them. Facilitating the interpretation of observations of behavior, physiology, mood, perceptual threshold, social indicator variables, and other responses, the book focuses on practical applications and requires much less mathematical background than most comparable texts. Using real data sets and currently available software (SPSS for Windows), the author employs extensive examples to clarify key concepts. Topics covered include research design issues, preliminary data screening, identification and description of cycles, summary of results across time series, and assessment of relations between time series. Also considered are theoretical questions, problems of interpretation, and potential sources of artifact.
Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
This volume contains a series of topical lectures in general relativity, cosmology, astrophysics, and field theory, with contributions from theorists and experimentalists.