A concise survey of essential topics in geophysical data processing for advanced undergraduate and graduate students in geophysics, environmental science, and engineering. With real-life scenarios and datasets, it shows how data processing techniques can be applied to real-world problems using detailed examples, illustrations, and exercises.
A concise survey of essential topics in geophysical data processing for advanced undergraduate and graduate students in geophysics, environmental science, and engineering. With real-life scenarios and datasets, it shows how data processing techniques can be applied to real-world problems using detailed examples, illustrations, and exercises.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Clark R. Wilson is the Carlton Centennial Professor of Geophysics at the University of Texas, Austin. After undergraduate studies in physics (University of California, San Diego) and graduate work in geophysics (Masters and PhD) at Scripps Institution of Oceanography, he joined the faculty of the Department of Geological Sciences at UT Austin. His research has ranged over diverse fields including applied seismology, space geodesy, and hydrology. He has twice served as Department Chair, and spent three years at NASA Headquarters overseeing programs in geodynamics and potential fields.
Inhaltsangabe
Preface 1. An Introduction With Geophysical Time Series Examples 2. Analog Signals and Digital Time Series 3. Sinusoids and Fourier Series 4. The Discrete Fourier Transform 5. Linear Systems and Digital Filters 6. Convolution and Related Theorems 7. Least Squares 8. Linear Filter Design 9. Least Square and Correlation Filters 10. Power and Coherence Spectra Appendix A. Matrices and Vectors Appendix B. Fourier Transforms of Continuous Functions Appendix C. Random Variable Concepts and Applications Appendix D. Further Reading Index.
Preface 1. An Introduction With Geophysical Time Series Examples 2. Analog Signals and Digital Time Series 3. Sinusoids and Fourier Series 4. The Discrete Fourier Transform 5. Linear Systems and Digital Filters 6. Convolution and Related Theorems 7. Least Squares 8. Linear Filter Design 9. Least Square and Correlation Filters 10. Power and Coherence Spectra Appendix A. Matrices and Vectors Appendix B. Fourier Transforms of Continuous Functions Appendix C. Random Variable Concepts and Applications Appendix D. Further Reading Index.
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