due to the complex physical properties of the detected targets using sonar systems, identification and classification of the actual targets is among the most difficult and complex issues of this field. considering the characteristics of the detected targets and unique capabilities of the intelligent methods in classification of their dataset, these methods seem to be the proper choice for the t...

This contribution describes a classification technique that improves the heart rate estimation during hemodialysis treatments. After the heart rate is estimated from the pressure signal of the dialysis machine, a classifier decides if it is correctly identified and rejects it if necessary. As the classifier employs a support vector machine, special interest is put on the automatic selection of ...

There is a substantial literature on the estimation of error rate, or risk, for nonparametric classifiers. Error-rate estimation has at least two purposes: accurately describing the error rate, and estimating the tuning parameters that permit the error rate to be mininised. In the light of work on related problems in nonparametric statistics, it is attractive to argue that both problems admit t...

1 The paper is based on our forthcoming book, Exchange Rate Regime, Choices and Consequences, MIT Press. The views expressed do not reflect the official views of the IMF.

This article considers a setting where embedded devices are used to acquire and classify images. Because of limited computing capacity, rely on parsimonious classification model with uneven accuracy. When local is deemed inaccurate, can decide offload the image an edge server more accurate but resource-intensive model. Resource constraints, e.g., network bandwidth, however, require regulating s...