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Informationen zum Autor J. Carlos Santamarina , Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0355, USA Dante Fratta , 3418H CEBA, Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA 70803, USA Klappentext Discrete Signals and Inverse Problems examines fundamental concepts necessary to engineers and scientists working with discrete signal processing and inverse problem solving, and places emphasis on the clear understanding of algorithms within the context of application needs. Based on the original ' Introduction to Discrete Signals and Inverse Problems in Civil Engineering ', this expanded and enriched version: combines discrete signal processing and inverse problem solving in one book covers the most versatile tools that are needed to process engineering and scientific data presents step-by-step 'implementation procedures' for the most relevant algorithms provides instructive figures, solved examples and insightful exercises Discrete Signals and Inverse Problems is essential reading for experimental researchers and practicing engineers in civil, mechanical and electrical engineering, non-destructive testing and instrumentation. This book is also an excellent reference for advanced undergraduate students and graduate students in engineering and science. Zusammenfassung Discrete Signals and Inverse Problems examines fundamental concepts necessary to engineers and scientists working with discrete signal processing and inverse problem solving! and places emphasis on the clear understanding of algorithms within the context of application needs. Inhaltsverzeichnis Preface xi Brief Comments on Notation xiii 1 Introduction 1 1.1 Signals, Systems, and Problems 1 1.2 Signals and Signal Processing - Application Examples 3 1.3 Inverse Problems - Application Examples 8 1.4 History - Discrete Mathematical Representation 10 1.5 Summary 12 Solved Problems 12 Additional Problems 14 2 Mathematical Concepts 17 2.1 Complex Numbers and Exponential Functions 17 2.2 Matrix Algebra 21 2.3 Derivatives - Constrained Optimization 28 2.4 Summary 29 Further Reading 29 Solved Problems 30 Additional Problems 33 3 Signals and Systems 35 3.1 Signals: Types and Characteristics 35 3.2 Implications of Digitization - Aliasing 40 3.3 Elemental Signals and Other Important Signals 45 3.4 Signal Analysis with Elemental Signals 49 3.5 Systems: Characteristics and Properties 53 3.6 Combination of Systems 57 3.7 Summary 59 Further Reading 59 Solved Problems 60 Additional Problems 63 4 Time Domain Analyses of Signals and Systems 65 4.1 Signals and Noise 65 4.2 Cross- and Autocorrelation: Identifying Similarities 77 4.3 The Impulse Response - System Identification 85 4.4 Convolution: Computing the Output Signal 89 4.5 Time Domain Operations in Matrix Form 94 4.6 Summary 96 Further Reading 96 Solved Problems 97 Additional Problems 99 5 Frequency Domain Analysis of Signals (Discrete Fourier Transform) 103 5.1 Orthogonal Functions - Fourier Series 103 5.2 Discrete Fourier Analysis and Synthesis 107 5.3 Characteristics of the Discrete Fourier Transform 112 5.4 Computation in Matrix Form 119 5.5 Truncation, Leakage, and Windows 121 5.6 Padding 123 5.7 Plots 125 5.8 The Two-Dimensional Discrete Fourier Transform 127 5.9 Procedure for Signal Recording 128 5.10 Summary 130 Further Reading and References 131 Solved Problems 131 Additional Problems 134 6 Frequency Domain Analysis of Systems 137 6.1 Sin...
