Signal analysis and signal treatment are integral parts of all types of Nuclear Magnetic Resonance. In the last ten years, much has been achieved in the development of dimensional spectra. At the same time new NMR techniques such as NMR Imaging and multidimensional spectroscopy have appeared, requiring entirely new methods of signal analysis. Up until now, most NMR texts and reference books limited their presentation of signal processing to a short introduction to the principles of the Fourier Transform, signal convolution, apodisation and noise reduction. To understand the mathematics of the newer signal processing techniques, it was necessary to go back to the primary references in NMR, chemometrics and mathematics journals. The objective of this book is to fill this void by presenting, in a single volume, both the theory and applications of most of these new techniques to Time-Domain, Frequency-Domain and Space-Domain NMR signals. Details are provided on many of the algorithms used and a companion CD-ROM is also included which contains some of the computer programs, either as source code or in executable form. Although it is aimed primarily at NMR users in the medical, industrial and academic fields, it should also interest chemometricians and programmers working with other techniques.

This book is about improving prohibited substances detection using the nuclear quadrupole resonance (NQR) technique at security checkpoints. The book proposes multiple signal processing and analysis techniques for improving detection of dangerous or contraband substances, such as explosives, narcotics, or toxic substances. Also, several hardware solutions are described and implemented in a custom-designed NQR spectrometer. A new approach to NQR signal detection is introduced using artificial intelligence/deep learning techniques. The book will be useful for for researchers and practitioners in the areas of electrical engineering, signal processing and analysis, applied spectroscopy, as well as for security or laboratory equipment manufacturers.

This reference/text contains the latest signal processing techniques in magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) for more efficient clinical diagnoses-providing ready-to-use algorithms for image segmentation and analysis, reconstruction and visualization, and removal of distortions and artifacts for increased detec

Signal Processing for Neuroscientists introduces analysis techniques primarily aimed at neuroscientists and biomedical engineering students with a reasonable but modest background in mathematics, physics, and computer programming. The focus of this text is on what can be considered the 'golden trio' in the signal processing field: averaging, Fourier analysis, and filtering. Techniques such as convolution, correlation, coherence, and wavelet analysis are considered in the context of time and frequency domain analysis. The whole spectrum of signal analysis is covered, ranging from data acquisition to data processing; and from the mathematical background of the analysis to the practical application of processing algorithms. Overall, the approach to the mathematics is informal with a focus on basic understanding of the methods and their interrelationships rather than detailed proofs or derivations. One of the principle goals is to provide the reader with the background required to understand the principles of commercially available analyses software, and to allow him/her to construct his/her own analysis tools in an environment such as MATLAB®. - Multiple color illustrations are integrated in the text - Includes an introduction to biomedical signals, noise characteristics, and recording techniques - Basics and background for more advanced topics can be found in extensive notes and appendices - A Companion Website hosts the MATLAB scripts and several data files: http://www.elsevierdirect.com/companion.jsp?ISBN=9780123708670

Matrix Singular Value Decomposition (SVD) and its application to problems in signal processing is explored in this book. The papers discuss algorithms and implementation architectures for computing the SVD, as well as a variety of applications such as systems and signal modeling and detection.The publication presents a number of keynote papers, highlighting recent developments in the field, namely large scale SVD applications, isospectral matrix flows, Riemannian SVD and consistent signal reconstruction. It also features a translation of a historical paper by Eugenio Beltrami, containing one of the earliest published discussions of the SVD.With contributions sourced from internationally recognised scientists, the book will be of specific interest to all researchers and students involved in the SVD and signal processing field.

NMR DATA PROCESSING Jeffrey C. Hoch and Alan S. Stern Nuclear Magnetic Resonance (NMR) spectroscopy is a powerful nondestructive technique for exploring the structure of matter. In recent years, NMR instrumentation has become increasingly sophisticated, and the software used to acquire and process NMR data continues to expand in scope and complexity. This software has always been difficult to understand, and, until now, it seemed likely to remain that way. NMR Data Processing examines and explains the techniques used to process, present, and analyze NMR data. It provides a complete account of the fundamentals of spectrum analysis and establishes a framework for applying those fundamentals to real NMR data. It also details, in clear and concise language, the basic principles underlying the complex software needed to analyze the data. Two chapters are devoted to the fundamentals and applications of discrete Fourier transform (DFT) in NMR, which was crucial to the development of modern NMR spectroscopy. A large part of the book focuses on increasingly important non-DFT methods, which obtain higher sensitivity and resolution. Other topics covered include: * Data formats * Processing for multidimensional experiments * Parametric modeling of NMR signals * Standard techniques-apodization, zero-filling, the Hilbert transform * Artifacts-aliasing, leakage, solvent signals * Advanced processing techniques-LP, MaxEnt, Bayesian analysis Jeffrey C. Hoch and Alan S. Stern conclude their in-depth look at this rapidly growing field by exploring methods for analyzing processed data, including visualization, quantification, and error analysis. Readers are provided with a solid foundation for developing new methods of their own. NMR Data Processing is an important tool for students learning basic principles for the first time, technicians troubleshooting data processing problems, and professional researchers developing new techniques. It will help all NMR users acquire a true grasp of the methods behind the process, avoid the pitfalls of misapplication and misinterpretation, and exploit the full power of NMR software.

Uses the FPT to Solve the Quantification Problem in MRSAn invaluable tool in non-invasive clinical oncology diagnosticsAddressing the critical need in clinical oncology for robust and stable signal processing in magnetic resonance spectroscopy (MRS), Signal Processing in Magnetic Resonance Spectroscopy with Biomedical Applications explores cutting-