title: Microstructure identification via detrended fluctuation analysis of ultrasound signals.
abstract: We describe an algorithm for simulating ultrasound propagation in random one-dimensional media, mimicking different microstructures by choosing physical properties such as domain sizes and mass densities from probability distributions. By combining a detrended fluctuation analysis (DFA) of the simulated ultrasound signals with tools from the pattern-recognition literature, we build a Gaussian classifier which is able to associate each ultrasound signal with its corresponding microstructure with a very high success rate. Furthermore, we also show that DFA data can be used to train a multilayer perceptron which estimates numerical values of physical properties associated with distinct microstructures.
authors.affiliation: Departamento de Engenharia Metalúrgica e de Materiais, Universidade Federal do Ceará, 60455-760, Fortaleza, CE, Brazil.
authors.forename: Paulo G
authors.initials: PG
authors.lastname: Normando
authors.forename: Romão S
authors.initials: RS
authors.lastname: Nascimento
authors.forename: Elineudo P
authors.initials: EP
authors.lastname: Moura
authors.forename: André P
authors.initials: AP
authors.lastname: Vieira