Many processes in nature arise from the interaction of periodic phenomena with random phenomena. The results are processes that are not periodic, but whose statistical functions are periodic functions of time. These processes are called cyclostationary and are an appropriate mathematical model for signals encountered in many fields including communications, radar, sonar, telemetry, acoustics, mechanics, econometrics, astronomy, and biology. Cyclostationary Processes and Time Series: Theory, Applications, and Generalizations addresses these issues and includes the following key features. Presents the foundations and developments of the second- and higher-order theory of cyclostationary signals Performs signal analysis using both the classical stochastic process approach and the functional approach for time series Provides applications in signal detection and estimation, filtering, parameter estimation, source location, modulation format classification, and biological signal characterization Includes algorithms for cyclic spectral analysis along with Matlab/Octave code Provides generalizations of the classical cyclostationary model in order to account for relative motion between transmitter and receiver and describe irregular statistical cyclicity in the data
This book also serves as a valuable reference for research statisticians and practitioners in areas of probability and statistics such as time series analysis, stochastic processes, and prediction theory.
Generalizations of Cyclostationary Signal Processing addresses these issues and includes the following key features: Presents the underlying theoretical framework, accompanied by details of their practical application, for the mathematical ...
By providing a comprehensive collection of contributions on the history and current state of the art in this rapidly emerging field, this book gives you a complete survey of the...
We should mention, the PARMA models are main discrete time series used to description of cyclostationary processes and appear to be useful in applications to vibration time series for machines that operate in time-varying ...
This book takes a middle course by emphasizing the time series models and their impact on spectrum analysis. The text begins with elements of probability theory and goes on to introduce the theory of stationary stochastic processes.
A best-seller in its print version, this comprehensive CD-ROM reference contains unique, fully searchable coverage of all major topics in digital signal processing (DSP), establishing an invaluable, time-saving resource for the engineering ...
The estimators of the harmonics H T of the variance 02 of a cyclostationary stochastic process can be obtained by first forming a sample variance of the time series xt. The sample variance is obtained by dividing the time series xt into ...
Constructions related to the skeleton, such as the cut locus, had been considered in the literature prior to Blum's work. However, Blum's eVorts revitalized interest in such descriptions and led to subsequent studies on the properties ...
This book gives the university researcher and R&D engineer insights into how to use TFSAP methods to develop and implement the engineering application systems they require.
This book is ideal for graduate students and researchers working with complex data in a range of research areas from communications to oceanography.