A Technique for Measuring Rotocraft Dynamic Stability in the 40 by 80 Foot Wind Tunnel

An on-line technique is described for the measurement of tilt rotor aircraft dynamic stability in the Ames 40- by 80-Foot Wind Tunnel. The technique is based on advanced system identification methodology and uses the instrumental variables approach. It is particulary applicable to real time estimation problems with limited amounts of noise-contaminated data. Several simulations are used to evaluate the algorithm. Estimated natural frequencies and damping ratios are compared with simulation values. The algorithm is also applied to wind tunnel data in an off-line mode. The results are used to develop preliminary guidelines for effective use of the algorithm

A summary of methods for analyzing nonstation- ary data

Estimation of nonstationary mean values, spectral density, and correlation functions - summary of methods for analyzing nonstationary dat

A Survey on Multisensor Fusion and Consensus Filtering for Sensor Networks

Multisensor fusion and consensus filtering are two fascinating subjects in the research of sensor networks. In this survey, we will cover both classic results and recent advances developed in these two topics. First, we recall some important results in the development ofmultisensor fusion technology. Particularly, we pay great attention to the fusion with unknown correlations, which ubiquitously exist in most of distributed filtering problems. Next, we give a systematic review on several widely used consensus filtering approaches. Furthermore, some latest progress on multisensor fusion and consensus filtering is also presented. Finally, conclusions are drawn and several potential future research directions are outlined.the Royal Society of the UK, the National Natural Science Foundation of China under Grants 61329301, 61374039, 61304010, 11301118, and 61573246, the Hujiang Foundation of China under Grants C14002 and D15009, the Alexander von Humboldt Foundation of Germany, and the Innovation Fund Project for Graduate Student of Shanghai under Grant JWCXSL140

A real time coincident indicator of the euro area business cycle

This paper is the result of the Bank of Italy-CEPR project to construct a monthly coincident indicator of the business cycle of the euro area. The index is estimated on the basis of a harmonized data set of monthly statistics of the euro area (951 series) which we constructed from a variety of sources. We use the information of this large panel to obtain an indicator which has three characteristics: (i) it provides real time information on monthly coincident activity since it is updated as new information become available in a non-synchronous way; (ii) it is cleaned from noise originated from measurement error and idiosyncratic national and sectoral dynamics; (iii) it is cleaned from seasonal and short-run dynamics through a Þlter that requires very little revision at the end of the sample. Unlike other methods used in the literature, the procedure takes into consideration the cross-country as well as the within-country correlation structure and exploits all information on dynamic cross-correlations. As a byproduct of our analysis, we provide a characterization of the commonality and dynamic relations of the series in the data set with respect to the coincident indicator and a dating of the euro area cycle.business cycle, dynamic factor model