Computational electromagnetics (CEM) involves modeling the interaction of electromagnetic fields with physical objects and their environment, such as the radiation emitted by antennas and the fields scattered from radar targets.

• Chapter 1: System Identification and Model-Based Parameter Estimation
• Chapter 2: A Brief Sampling of System Identification and Model-Based Parameter Estimation Applications in Various Disciplines
• Chapter 3: Mathematical Background of MBPE
• Chapter 4: Sampling Strategies for Effective Implementation of Prony's Method
• Chapter 5: Conserving Waveform Information Content in the Spectral Domain using Prony's Method
• Chapter 6: Minimizing the Number of Frequency Samples Needed to Represent a Transfer Function Using Adaptive Sampling
• Chapter 7: Using Prony's Method to Design Arrays that Produce the Patterns of Continuous Source Distributions and Prescribed Radiation Patterns
• Chapter 8: Designing Discrete Arrays Using Prony's Method to Model Exponentiated Radiation Patterns
• Chapter 9: Using Adaptive Estimation to Minimize the Number of Samples Needed to Develop a Radiation or Scattering Pattern to a Specified Uncertainty
• Chapter 10: Modeling Dipole Arrays that Produce Synthesized Patterns Using NEC
• Chapter 11: Using Model-Based Parameter Estimation to Assess the Accuracy of Numerical Models
• Chapter 12: Using Prony's Method to Develop Pole-Based Models of Linear Sources
• Chapter 13: Inversion of One-Dimensional Scattering Data Using Prony's Method
• Chapter 14: Derivative Sampling of Computational Data
• Appendix A: MBPE estimation in computational electromagnetics
• Appendix B: Symbols and Notation
• Appendix C: MBPE References