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We propose a partition-based state estimator for linear discrete-time systems composed by coupled subsystems affected by bounded disturbances. The architecture is distributed in the sense that each subsystem is equipped with a local state estimator that ex ...
This paper addresses road traffic monitoring using passive acoustic sensors. Recently, the feasibility of the joint speed and wheelbase length estimation of a road vehicle using particle filtering has been demonstrated. In essence, the direction of arrival ...
In this paper we propose a novel partition-based state estimator for linear discrete-time systems composed of physically coupled subsystems affected by bounded disturbances. The proposed scheme is distributed in the sense that each local state estimator ex ...
We study a new image sensor that is reminiscent of traditional photographic film. Each pixel in the sensor has a binary response, giving only a one-bit quantized measurement of the local light intensity. To analyze its performance, we formulate the oversam ...
Institute of Electrical and Electronics Engineers2012
This paper investigates detection of English keywords in a conversational scenario using a combination of acoustic and LVCSR based keyword spotting systems. Acoustic KWS systems search predefined words in parameterized spoken data. Corresponding confidence ...
This paper investigates detection of English keywords in a conversational scenario using a combination of acoustic and LVCSR based keyword spotting systems. Acoustic KWS systems search predefined words in parameterized spoken data. Corresponding confidence ...
The trends in the design of image sensors are to build sensors with low noise, high sensitivity, high dynamic range, and small pixel size. How can we benefit from pixels with small size and high sensitivity? In this dissertation, we study a new image senso ...
Detection of anomalies is a broad field of study, which is applied in different areas such as data monitoring, navigation, and pattern recognition. In this paper we propose two measures to detect anomalous behaviors in an ensemble of classifiers by monitor ...
This paper introduces a novel batch optimization based calibration framework for legged robots. Given a nondegenerate calibration dataset and considering the stochastic models of the sensors, the task is formulated as a maximum likelihood problem. In order ...
Composite likelihoods are increasingly used in applications where the full likelihood is analytically unknown or computationally prohibitive. Although some frequentist properties of the maximum composite likelihood estimator are akin to those of the maximu ...
Academia Sinica, Institute of Statistical Science2012
