Radar-based Feature Design and Multiclass Classification for Road User Recognition

The classification of individual traffic participants is a complex task, especially for challenging scenarios with multiple road users or under bad weather conditions. Radar sensors provide an - with respect to well established camera systems - orthogonal way of measuring such scenes. In order to gain accurate classification results, 50 different features are extracted from the measurement data and tested on their performance. From these features a suitable subset is chosen and passed to random forest and long short-term memory (LSTM) classifiers to obtain class predictions for the radar input. Moreover, it is shown why data imbalance is an inherent problem in automotive radar classification when the dataset is not sufficiently large. To overcome this issue, classifier binarization is used among other techniques in order to better account for underrepresented classes. A new method to couple the resulting probabilities is proposed and compared to others with great success. Final results show substantial improvements when compared to ordinary multiclass classificationComment: 8 pages, 6 figure

Linear Control Theory with an ℋ∞ Optimality Criterion

This expository paper sets out the principal results in ℋ∞ control theory in the context of continuous-time linear systems. The focus is on the mathematical theory rather than computational methods

A Comparison of AVIRIS and Landsat for Land Use Classification at the Urban Fringe

In this study we tested whether AVIRIS data allowed for improved land use classification over synthetic Landsat ETM+ data for a location on the urban-rural fringe of Colorado. After processing the AVIRIS image and creating a synthetic Landsat image, we used standard classification and post-classification procedures to compare the data sources for land use mapping. We found that, for this location, AVIRIS holds modest, but real, advantages over Landsat for the classification of heterogeneous and vegetated land uses. Furthermore, this advantage comes almost entirely from the large number of sensor spectral bands rather than the high Signal-to-Noise Ratio (SNR)

A Model of Housing Stock for Canada

Using an error-correction model (ECM) framework, the authors attempt to quantify the degree of disequilibrium in Canadian housing stock over the period 1961–2008 for the national aggregate and over 1981–2008 for the provinces. They find that, based on quarterly data, the level of housing stock in the long run is associated with population, real per capita disposable income, and real house prices. Population growth (net migration, particularly for the western provinces) is also an important determinant of the short-run dynamics of housing stock, after controlling for serial correlation in the dependent variable. Real mortgage rates, consumer confidence, and a number of other variables identified in the literature are found to play a small role in the short run. The authors’ model suggests that the Canadian housing stock was 2 per cent above its equilibrium level at the end of 2008. There was likely overbuilding, to varying degrees, in Saskatchewan, New Brunswick, British Columbia, Ontario, and Quebec.Domestic demand and components

Determinacy and Learnability of Monetary Policy Rules in Small Open Economies

This paper evaluates under which conditions different Taylor-type rules lead to determinacy and expectational stability (E-stability) of rational expectations equilibrium in a simple New Keynesian small open economy model, developed by Gali and Monacelli (2005). In particular, we extend the Bullard and Mitra (2002) results of determinacy and E-stability in a closed economy to this small open economy framework. Our results highlight an important link between the Taylor principle and both determinacy and learnability of equilibrium in small open economies. More importantly, the degree of openness coupled with the nature of the policy rule adopted by the monetary authorities might change this link in important ways. A key finding is that, contrary to Bullard and Mitra, expectations-based rules that involve the CPI and/or the nominal exchange rate limit the region of E-stability and the Taylor Principle does not guarantee E-stability. We also show that some forms of managed exchange rate rules can help to alleviate problems of both indeterminacy and expectational instability, yet these rules might not be desirable since they promote greater volatility in the economy.

Algebraic methods for dynamic systems

Algebraic methods for application to dynamic control system