The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In order to develop an automatic target identification system for underwater objects, it is necessary to extract and classify the features contained in waves scattered from the targets. According to the acoustic scattering theory, the scattered signal contains the “signatures” corresponding to the structure and material content of the target. Pseudo-Wigner Distribution (PWD) function is applied on...
Use of competitive learning techniques towards the area of fault detection is being investigated. The objective of Fault Detection and Identification (FDI) is to detect, isolate and identify faults so that the system performance can be improved. This paper is focused on the data driven approach for fault detection and would use: (i) Unsupervised Competitive Learning, (ii) Conscience Learning and (iii)...
This paper discusses the use of unsupervised learning and localized modeling to identify nonlinear dynamical systems from empirical series data. A finite-order nonlinear autoregressive (AR) model is constructed to capture the system dynamics. The embedded input space for the nonlinear AR model is partitioned into overlapped regions that are fine enough so that localized modeling techniques, such as...
This paper introduces a novel underwater target classification scheme which recognizes underwater ordnances based on their backscattered Time-Frequency (TF) signatures. The objective is to automatically identify the shape and interior content of sea-disposed underwater munitions and ordnance found in the Hawaiian coastlines. This effort helps in the removal of the above sea-disposals from the ocean...
One aspect of modern commercial aircraft engine maintenance involves monitoring recorded engine parameters. When these parameters exceed their respective threshold tolerances, appropriate maintenance actions are taken. Reducing these unscheduled maintenance actions would allow maintainers to more effectively plan their maintenance schedules which help in the reduction of costs. One way of accomplishing...
This paper discusses the use of unsupervised learning and localized modeling to identify nonlinear dynamical systems from empirical data. A finite-order nonlinear autoregressive (AR) model is constructed to capture the system dynamics. The embedded input space for the nonlinear AR model is partitioned into overlapped regions that are fine enough so that localized modeling techniques, such as local...
In this paper, a strategy of failure detection, identification and reconfigurable scheme for a dynamic system is proposed. The proposed scheme provides detection and identification of sensor, actuator and/or system component failures, dynamic system state estimation and system performance recovery. Fault detection and identification is carried out using radial basis function (RBF) neural network and...
This paper will present a robust extended Kalman filter (REKF) applied to the navigation of an autonomous underwater vehicle (AUV) using robust Simultaneous Localization and Mapping (SLAM) techniques. Conventional Kalman Filter methods suffer from the assumption of Gaussian noise statistics, which often lead to failures when these assumptions do not hold. Additionally, the linearization errors associated...
In this paper we study the discrete generalized Lyapunov equation for implicit systems. We show how the anticipation phenomenon and the asymptotic stability of the system can be studied in terms of the solutions to the discrete generalized Lyapunov equation. We further study under which conditions these solutions are unique. Numerical examples are provided to illustrate the results presented.
In this paper we study the discrete generalized Lyapunov equation for implicit systems. We show how the anticipation phenomenon and the asymptotic stability of the system can be studied in terms of the solutions to the discrete generalized Lyapunov equation. We further study under which conditions these solutions are unique. Numerical examples are provided to illustrate the results presented.
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.