Bridge the gap between signal processing and analytical chemistry with this essential guide

Analytical chemistry relies on increasingly sophisticated technology for deriving data from images or signals. Recent technological innovations have only deepened the relationship between chemical analysis and signal processing, but they have also introduced new challenges in identifying and characterizing particular data points from within a mixed-source dataset. An innovative technique called Blind Source Separation (BSS) can isolate and retrieve the individual sources for a mixed-source data array, allowing for refined analysis that fully exploits these cutting-edged imaging and signal-sensing technologies.

Source Separation in Physical-Chemical Sensing supplies a thorough introduction to the principles of BSS and its potential applications in analytical chemistry. Designed to bridge the gap between chemical analysis and signal processing, it promises to be invaluable in both fields. Its alertness to the latest technologies and the full range of potential BSS applications makes it an indispensable introduction to this cutting-edge method.

Source Separation in Physical-Chemical Sensing readers will also find:

• A database of signals from analytical chemistry to facilitate processing and analysis
• Detailed treatment of source separation in potentiometric sensors, hyperspectral imaging, and others
• Thorough discussion of Bayesian source separation, tensorial methods, geometrical methods, and more

Source Separation in Physical-Chemical Sensing isa must-have for researchers and engineers working in signal processing and statistical analysis, as well as for chemists and physicists looking to apply source separation.

Christian Jutten, PhD, is Professor and Senior Member of Image and Signal Processing at the Institut Universitaire de France, Epernay, France. He was previously Full Professor at Université Joseph Fourier, Grenoble, Switzerland. He is globally recognized for his pioneering research contributions to blind source separation, and has published widely on this and related subjects.

Leonardo Tomazelli Duarte, PhD, is Professor of Applied Sciences in the Faculty of Electrical and Computer Engineering, State University of Campinas, Brazil. He has researched extensively into blind source separation and other aspects of signal processing technology.

Saïd Moussaoui, PhD, is a Researcher and Associate Professor of Algorithms and Computational Theory at École Centrale de Nantes, France. He has published widely on signal processing, source separation, and other related subjects.