This e-book presents several research areas of elliptical problems solved by differential equations. The mathematical models explained in this e-book have been contributed by experts in the field and can be applied to a wide range of real life examples. Methods explained include pre-conditioned conjugate grid models, higher order discretization and finite element mesh generation. This e-book should be a useful reference for scholars and professionals interested in elliptical partial differential equations.

Real and complex exponential data fitting is an important activity in many different areas of science and engineering, ranging from Nuclear Magnetic Resonance Spectroscopy and Lattice Quantum Chromodynamics to Electrical and Chemical Engineering, Vision and Robotics. The most commonly used norm in the approximation by linear combinations of exponentials is the l2 norm (sum of squares of residuals), in which case one obtains a nonlinear separable least squares problem. A number of different methods have been proposed through the years to solve these types of problems and new applications appear daily. Necessary guidance is provided so that care should be taken when applying standard or simplified methods to it. The described methods take into account the separability between the linear and nonlinear parameters, which have been quite successful. The accessibility of good, publicly available software that has been very beneficial in many different fields is also considered. This Ebook covers the main solution methods (Variable Projections, Modified Prony) and also emphasizes the applications to different fields. It is considered essential reading for researchers and students in this field.

Fundamentals of Mathematics in Medical Research: Theory and Cases is a comprehensive guide to the mathematical principles and methods used in medical research. This book is structured to facilitate learning and application and gives a solid foundation to readers. The book is divided into multiple parts that explain basic concepts in a progressive way. - Part I covers real-valued functions of one or more variables with geometric representations to establish a core understanding of advanced mathematics - Part II covers inferential methods of probability and statistics from basic probability to parametric and nonparametric tests - Part III covers correlation theory and advanced analysis of real-valued functions - Part IV covers multivariable analysis for solving complex problems with an explanation of Markov Chain models - An Appendix provides solutions for all exercises and along with Fortran 90 programs, Python scripts and Linux scripts to explore the mathematical concepts explained in the book. Key Features: Introduction and Conclusion in Every Chapter Exercises and Solutions Program codes and scripts Comprehensive Coverage of Mathematics for Academics and Research Real-World Cases This book is an essential resource for researchers, students, and professionals in medicine and allied fields who seek to understand and apply mathematical methods in their work.