1,721,055 research outputs found
Electromagnetic Environmental Pollution Monitoring: Source Localization by the Independent Component Analysis
No full text`Mechanical' neural learning and InfoMax Orthonormal Independent Component Analysis
No full textWith this paper we aim to present a new class of learning models for linear as well as non-linear neural layers, deriving from the study of the dynamics of an abstract rigid mechanical system. The set of equations describing the motion of this system may be readily interpreted as a learning rule for orthogonal networks. As a simple example of how to use the new learning theory, a case of Orthonormal Independent Component Analysis based on the Bell-Sejnowski's InfoMax principle is discussed through simulations
Analytical Results on Pseudo-Polynomial Functional-Link Neurons for Blind Density Shaping
No full textNeural network approach to maximum likelihood estimation for eddy-current back-scattering NDE data inversion
No full textThe aim of this paper is to present a neural network approach to crack location based on eddy-current back-scattering measured data inversion. A deep defect inside a conductive object may be revealed by sliding an electromagnetic probe over the object's accessible surface: this operation gives a set of differential impedance measures, whose configuration carries information on both the shape and the location of the crack. By inverting the measured impedance data it is thus possible to reconstruct the geometry of the defect. Commonly employed data inversion techniques, such as the one based on maximum likelihood theory, require the availability of a forward model which describes the way the data are generated by the system under test. When a physical model is not available or is too much difficult to be handled, a suitable black-box model could be used instead. In this paper we propose the use of a multilayer perceptron for this purpose, which proved to be effective because of its well-known function approximation and system identification capabilities
ECT-Data Fusion by the Independent Component Analysis for Non-Destructuve Evaluation of Metallic Slabs
No full textNonsymmetric PDF approximation by artificial neurons: application to statistical characterization of reinforced composites
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