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.
Myopic information-based approaches maximizing information gain for single one observation opportunity are effective to search for multiple moving targets in ocean surveillance by space-based sensors. A non-myopic approach based on reinforcement learning is developed in order to maximize information gain for the long term. Reinforcement learning adjusts optimal control policy and learns system behaviors...
Aiming at difficulty modeling of large amounts of industrial process data, a novel soft sensor model based on artificial immune agent-based multiple model Radial Basis Function (RBF) networks is proposed in this paper. The method is to predict the qualities of manufactured products of Crude Oil Tower. In the IMMST-Team system, some biological immune based operation and learning rules which can efficiently...
Neuromodulation is thought to be one of the underlying principles of learning and memory in biological neural networks. Recent experiments have shown that neuroevolutionary methods benefit from neuromodulation in simple grid-world problems. In this paper we investigate the performance of a neuroevolutionary method applied to a more realistic robotic task. While confirming the favorable effect of neuromodulatory...
The neural extended Kalman filter (NEKF) has proven to be a quality maneuver target tracking system when the sensors provide a fully observable measurement, such as a radarpsilas range-bearing measurement or a position report. As with any state estimation technique, the NEKF requires observability in order to estimate the target track states. Observability is needed as well to train the weights of...
Learning-from-Examples (LfE) algorithms are becoming popular building blocks for some type of measurement systems, like smart sensors. They enhance and extend the measurement capabilities of sensors allowing the use of sophisticated algorithms for sensor compensation, or for the automatic classification of physical phenomena. Machine learning systems differ quite a bit from components more commonly...
Designing less intrusive intelligent environments requires a deep understanding of activities that a user is engaged in. This paper presents a novel one-pass neural network system that uses unobtrusive and relatively simple sensors and puts forward a constructive algorithm which is able to recognize different high level activities (such as ldquosleepingrdquo, ldquowashingrdquo, ldquoworking at computerrdquo)...
An application of the power of neural networks in the implementation of a novel sensor for classification of material type and its surface properties by means of a lightweight plunger probe and optical mouse sensor is presented in this paper. An experimental prototype was developed which involves bouncing or hopping of the plunger-based impact probe freely on the plain surface of an object under test...
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.