一种基于判决反馈的OFDM系统载波频率跟踪算法

研究了多径信道下OFDM系统的一种新的载波频率跟踪算法，这种算法以判决反馈和接收端的时域信号重构为基础。推导了估计结果的精确解，比较了使用原估计结果和新的估计结果进行频偏补偿时系统跟踪性能的不同。通过对算法的仔细分析，发现除了通常的加性噪声外，信道估计误差、子载波数目和子载波的调制方式也影响频偏的估计结果和跟踪范围，而且子载波的数目和调制方式是决定性的因素。这种频率跟踪方法的优点是即使在很低的信噪比下仍然能获得高的跟踪精度，且实现相对简单。     

Representation of shift-invariant operators onL 2 byH ∞ transfer functions: An elementary proof,a generalization toL p,and a counterexample forL ∞

We give an elementary proof of the well-known fact that shift-invariant operators onL ²[0, ∞) are represented by transfer functions which are bounded and analytic on the right open half-plane. We prove a generalization to Banach space-valuedL ^p -functions, where 1≤p<∞. We show that the result no longer holds forp=∞. This research was supported partially by the Weizmann Fellowship, and partially by the Air Force Office of Scientific Research under Contract F49620-86-C-0111.     

Observer design for autonomous discrete-time nonlinear systems

We obtain a necessary and sufficient condition for a discrete-time nonlinear system to be locally state equivalent to the nonlinear observer form. The result looks similar to the continuous counterpart except for the fact that Ad-operation is utilized instead of ad-operation.     

Stabilization of fixed modes in expansions of LTI systems

The objective of this note is to propose a method for stabilization of structurally fixed modes in expansions of LTI dynamic systems in the scope of overlapping decentralized control design based on the expansion/contraction framework, enabling successful design for a broader class of problems than considered so far. The method is based on a judicious choice of complementary matrices in the expanded space. Numerical examples are provided to illustrate simplicity and efficiency of the proposed approach.     

Tribotronics—Towards active tribology

A constant trend towards more compact mechanical systems with higher power densities and increased thermo-mechanical loads emphasises the importance of the development of new design approaches and novel tribological systems. Ignoring this may cause a significant slow down in technological and industrial development. Tribotronics or active tribology based on adaptive performance is thought of as being critical in the implementation of smart machine concepts. Recognition of the importance of tribotronics, or active control of system loss outputs, such as those through friction and wear will have significant beneficial economic consequences as a result of the associated accelerated rate of technological progress. These smart tribotronic systems can be embedded in a great variety of machines and mechanisms. If this integration is made at the design stage, products that are more flexible, efficient and reliable can be produced. The concept of tribotronics is presented and discussed in this paper. Some illustrative examples that show the feasibility of an “active” approach are given. In addition, various possibilities already reported in literature are discussed.     

Florida DOT Project-Level Bridge Management Models

The Florida Department of Transportation (FDOT) is in the process of implementing Pontis, a Bridge Management System, to provide decision support to engineers in the headquarters and district offices as they make routine policy, programming, and budgeting decisions regarding the preservation and improvement of the state’s bridges. As part of this effort, an ongoing research program is underway to adapt the system to FDOT needs as well as to advance the state of the art in several areas important to the Department. Most of the research results are organized around a new project-level decision support framework that complements and builds on Pontis’ existing network-level analysis. Specific new models include accident risk and user cost due to roadway width and alignment deficiencies; user cost of load capacity and vertical clearance restrictions, and moveable bridge openings; project-level prediction models for bridge element condition and costs; and prediction of economics of scale and scoping possibilities. The new models are built into a highly graphical spreadsheet model for decision support use.     

Passivity‐based sliding mode control for nonlinear systems

Passivity with sliding mode control for a class of nonlinear systems with and without unknown parameters is considered in this paper. In fact, a method for deriving a nonlinear system with external disturbances to a passive system is considered. Then a passive sliding mode control is designed corresponding to a given storage function. The passivity property guarantees the system stability while sliding mode control techniques assures the robustness of the proposed controller. When the system includes unknown parameters, an appropriate updated law is obtained so that the new transformed system is passive. The passivation property of linear systems with sliding mode is also analysed. The linear and nonlinear theories are applied to a simple pendulum model and the gravity‐flow/pipeline system, respectively. Copyright © 2008 John Wiley & Sons, Ltd.     

Extending boosting for large scale spoken language understanding

We propose three methods for extending the Boosting family of classifiers motivated by the real-life problems we have encountered. First, we propose a semisupervised learning method for exploiting the unlabeled data in Boosting. We then present a novel classification model adaptation method. The goal of adaptation is optimizing an existing model for a new target application, which is similar to the previous one but may have different classes or class distributions. Finally, we present an efficient and effective cost-sensitive classification method that extends Boosting to allow for weighted classes. We evaluated these methods for call classification in the AT&;T VoiceTone^® spoken language understanding system. Our results indicate that it is possible to obtain the same classification performance by using 30% less labeled data when the unlabeled data is utilized through semisupervised learning. Using model adaptation we can achieve the same classification accuracy using less than half of the labeled data from the new application. Finally, we present significant improvements in the “important” (i.e., higher weighted) classes without a significant loss in overall performance using the proposed cost-sensitive classification method.