The use of machine learning in smart antennas

The goal here is to make arrays smart so that when one of the antenna elements in the array fails, the beamforming and beamsteering performance of the array degrades gracefully. Such an objective can be achieved in reconfiguring the array when an element is found to be defective, by either changing the material properties of the substrate or by applying appropriate loading in order to make the array functional again. Our approach is based on optimization using machine learning and support vector machines (SVM). The basic idea is to change the excitation coefficient for each array element (magnitude and phase) to optimize for changes due to the environment surrounding an array antenna. Using support vector machines, one can train the antenna array to change its elements\u27 phase or excitation distribution in order to maintain a certain radiation pattern or to enhance its beamsteering and ing properties and solve the DOA problem as well

Masters and Novices

On 5–6 June 2005, the Electrical and Computer Engineering Department of the University of New Mexico organized a workshop to celebrate the career of Peter Dorato. The event was held at Los Poblanos Inn, an historic inn and cultural center located in the village of Los Ranchos de Albuquerque, New Mexico. Los Poblanos Inn, which is listed on both the New Mexico and National Registers of Historic Places, has 25 acres of agricultural fields and extensive historic gardens. Both Los Poblanos Inn and La Quinta Cultural Center were designed by the Southwest’s foremost architect John Gaw Meem, the “father of Santa Fe style.

Experimental results on the effects of 802.11 b WLAN on networked control system

In this paper we expose theoretically and experimentally some of issues induced by wireless Ethernet when it is used to transmit plant state information to the controller, and control signals to the plant, in a closed-loop system. We also propose some compensation actions, and evaluate their performance in the experimental set up

2009 Index IEEE Antennas and Wireless Propagation Letters Vol. 8

This index covers all technical items - papers, correspondence, reviews, etc. - that appeared in this periodical during the year, and items from previous years that were commented upon or corrected in this year. Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author\u27s name. The primary entry includes the coauthors\u27 names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author\u27s name, the publication abbreviation, month, and year, and inclusive pages. Note that the item title is found only under the primary entry in the Author Index

Model-based networked control for nonlinear systems with stochastic packet dropout

In this paper we analyze model-based networked control systems for a discrete-time nonlinear plant model, operating in the presence of stochastic dropout of state observations. The dropout is modelled as a Markov chain, and sufficient conditions for stability are provided using the stochastic version of Lyapunov\u27s second method

2008 Index IEEE Transactions on Control Systems Technology Vol. 16

This index covers all technical items - papers, correspondence, reviews, etc. - that appeared in this periodical during the year, and items from previous years that were commented upon or corrected in this year. Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author\u27s name. The primary entry includes the coauthors\u27 names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author\u27s name, the publication abbreviation, month, and year, and inclusive pages. Note that the item title is found only under the primary entry in the Author Index

Finite-Time Control of Uncertain Linear Systems Using Statistical Learning Methods

In this paper we show how some difficult linear algebra problems can be “approximately” solved using statistical learning methods. We illustrate our results by considering the state and output feedback, finite-time robust stabilization problems for linear systems subject to time-varying norm-bounded uncertainties and to unknown disturbances. In the state feedback case, we have obtained in an earlier paper, a sufficient condition for finite-time stabilization in the presence of time-varying disturbances; such condition requires the solution of a Linear Matrix Inequality (LMI) feasibility problem, which is by now a standard application of linear algebraic methods. In the output feedback case, however, we end up with a Bilinear Matrix Inequality (BMI) problem which we attack by resorting to a statistical approach

Symposium on Systems, Control, and Networks in Honor of Professor Pravin Varaiya on His 65th Birthday

The Symposium on Systems, Control, and Networks was held on 5–7 June 2005 in Berkeley, California, in honor of Prof. Pravin Varaiya on the occasion of his 65th birthday. Pravin Varaiya has been on the faculty of the Department of Electrical Engineering and Computer Sciences of the University of California, Berkeley, since he completed his Ph.D. there in 1966

Distributed joint rate and power control game-theoretic algorithms for wireless data

In this letter, we consider two distributed game theoretic algorithms to jointly solve the problem of optimizing the transmission rates and transmit powers for future wireless data communication systems. We then establish the existence, uniqueness and Pareto optimality of Nash equilibria of both games