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In this paper an algorithm for nonlinear explicit model predictive control is introduced based on multiresolution function approximation that returns a low complexity approximate receding horizon control law built on a hierarchy of second order interpolets ...
Determining safe aircraft trajectories that avoid hazardous weather regions and other aircraft while efficiently using the available airspace is an important problem. Although tactical weather forecast maps have been available, their use in automated aircr ...
In this paper, a new framework to discover places-of-interest from multimodal mobile phone data is presented. Mobile phones have been used as sensors to obtain location information from users’ real lives. Two levels of clustering are used to obtain place ...
We revisit the topics of near-field adaptive beamforming and source localization following an alternative approach based on a spatio- temporal spectral representation of the acoustic wave field. With the proposed method, the wave field is expressed as a se ...
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In this study, we derive a fast, novel time-domain algorithm to compute the nth-order moment of the power spectral density of the photoelectric current as measured in laser-Doppler flowmetry (LDF). It is well established that in the LDF literature these mo ...
Feedback error-related potentials are a promising brain process in the field of rehabilitation since they are related to human learning. Due to the fact that many therapeutic strategies rely on the presentation of feedback stimuli, potentials generated by ...
Spectral prediction models for halftone prints generally assume homogeneously thick and sharply edged ink dots, i.e., bilevel halftones. In real prints, the ink thickness often decreases at the boundaries of the ink dots, thereby forming continuous-level h ...
We revisit an original concept of speech coding in which the signal is separated into the carrier modulated by the signal envelope. A recently developed technique, called frequency-domain linear prediction (FDLP), is applied for the efficient estimation of ...
A high-resolution multi-sensor and multi-polarization Ground Penetrating Radar (GPR) dataset was acquired on a concrete retaining wall. This dataset was characterised as a low pass filter with the help of a moving window spectral analysis. In order to exam ...
Generalized Linear Models (GLMs) are an increasingly popular framework for modeling neural spike trains. They have been linked to the theory of stochastic point processes and researchers have used this relation to assess goodness-of-fit using methods from ...