Expanded to cover more advanced applications where statistical properties of data can be nonstationary and the physical systems nonlinear as opposed to only linear. Stresses the practical use and interpretation of analyzed data to solve problems. Special attention is given to bias and random errors involved in desired estimates and the proper interpretation of results from specific applications. Includes numerous case studies concerned with dynamic problems which can occur in a variety of fields.
Probability Functions and Amplitude Measures Correlation and Spectral Density Functions Single-Input/Single-Output Relationships System Identification and Response Propagation-Path Identification Single-Input/Multiple-Output Problems Multiple-Input/Multiple-Output Relationships Energy-Source Identification Procedures to Solve Multiple-Input/Multiple-Output Problems Statistical Errors in Estimates Nonstationary Data Analysis Techniques Nonlinear System Analysis Techniques References List of Figures List of Tables Index Glossary of Symbols.