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.
This paper deals with applications of artificial immune systems techniques for node positioning in wireless sensor networks of industrial plants. The proposed model is discussed and some preliminary results are presented.
This paper describes a neural network based equalizer trained by the artificial immune system learning algorithm. The equalizer takes advantage of the characteristics of neural nets and artificial immune systems. Simulations for channel responses examples indicate the usefulness of the proposed equalizer.
This paper deals with node positioning for wireless industrial plants using artificial immune systems. The proposed model is described as well as some preliminary results indicating the success of the approach.
This paper shows an enhanced training for the EKF-RTRL (Extended Kalman Filter - Real Time Recurrent Learning) single neuron Equalizer using heuristic mechanisms on the training algorithms enabling them to make the training process initial conditions set-up more automatic. The method uses a parameter which evolves accordingly in the training period. The equalizer is used for fast fading selective...
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.