103,366 research outputs found
Spatial Filtering Pipeline Evaluation of Cortically Coupled Computer Vision System for Rapid Serial Visual Presentation
Rapid Serial Visual Presentation (RSVP) is a paradigm that supports the
application of cortically coupled computer vision to rapid image search. In
RSVP, images are presented to participants in a rapid serial sequence which can
evoke Event-related Potentials (ERPs) detectable in their Electroencephalogram
(EEG). The contemporary approach to this problem involves supervised spatial
filtering techniques which are applied for the purposes of enhancing the
discriminative information in the EEG data. In this paper we make two primary
contributions to that field: 1) We propose a novel spatial filtering method
which we call the Multiple Time Window LDA Beamformer (MTWLB) method; 2) we
provide a comprehensive comparison of nine spatial filtering pipelines using
three spatial filtering schemes namely, MTWLB, xDAWN, Common Spatial Pattern
(CSP) and three linear classification methods Linear Discriminant Analysis
(LDA), Bayesian Linear Regression (BLR) and Logistic Regression (LR). Three
pipelines without spatial filtering are used as baseline comparison. The Area
Under Curve (AUC) is used as an evaluation metric in this paper. The results
reveal that MTWLB and xDAWN spatial filtering techniques enhance the
classification performance of the pipeline but CSP does not. The results also
support the conclusion that LR can be effective for RSVP based BCI if
discriminative features are available
Feedback control of quantum state reduction
Feedback control of quantum mechanical systems must take into account the probabilistic nature of quantum measurement. We formulate quantum feedback control as a problem of stochastic nonlinear control by considering separately a quantum filtering problem and a state feedback control problem for the filter. We explore the use of stochastic Lyapunov techniques for the design of feedback controllers for quantum spin systems and demonstrate the possibility of stabilizing one outcome of a quantum measurement with unit probability
Frame Combination Techniques for Ultra High-Contrast Imaging
We summarize here an experimental frame combination pipeline we developed for
ultra high-contrast imaging with systems like the upcoming VLT SPHERE
instrument. The pipeline combines strategies from the Drizzle technique, the
Spitzer IRACproc package, and homegrown codes, to combine image sets that may
include a rotating field of view and arbitrary shifts between frames. The
pipeline is meant to be robust at dealing with data that may contain non-ideal
effects like sub-pixel pointing errors, missing data points, non-symmetrical
noise sources, arbitrary geometric distortions, and rapidly changing point
spread functions. We summarize in this document individual steps and
strategies, as well as results from preliminary tests and simulations.Comment: 9 pages, 4 figures, SPIE conference pape
Oversampling PCM techniques and optimum noise shapers for quantizing a class of nonbandlimited signals
We consider the efficient quantization of a class of nonbandlimited signals, namely, the class of discrete-time signals that can be recovered from their decimated version. The signals are modeled as the output of a single FIR interpolation filter (single band model) or, more generally, as the sum of the outputs of L FIR interpolation filters (multiband model). These nonbandlimited signals are oversampled, and it is therefore reasonable to expect that we can reap the same benefits of well-known efficient A/D techniques that apply only to bandlimited signals. We first show that we can obtain a great reduction in the quantization noise variance due to the oversampled nature of the signals. We can achieve a substantial decrease in bit rate by appropriately decimating the signals and then quantizing them. To further increase the effective quantizer resolution, noise shaping is introduced by optimizing prefilters and postfilters around the quantizer. We start with a scalar time-invariant quantizer and study two important cases of linear time invariant (LTI) filters, namely, the case where the postfilter is the inverse of the prefilter and the more general case where the postfilter is independent from the prefilter. Closed form expressions for the optimum filters and average minimum mean square error are derived in each case for both the single band and multiband models. The class of noise shaping filters and quantizers is then enlarged to include linear periodically time varying (LPTV)M filters and periodically time-varying quantizers of period M. We study two special cases in great detail
Adaptive pre-filtering techniques for colour image analysis
One important step in the process of colour image
segmentation is to reduce the errors caused by image
noise and local colour inhomogeneities. This can be
achieved by filtering the data with a smoothing
operator that eliminates the noise and the weak
textures. In this regard, the aim of this paper is to
evaluate the performance of two image smoothing
techniques designed for colour images, namely
bilateral filtering for edge preserving smoothing and
coupled forward and backward anisotropic diffusion
scheme (FAB). Both techniques are non-linear and
have the purpose of eliminating the image noise,
reduce weak textures and artefacts and improve the
coherence of colour information. A quantitative
comparison between them will be evaluated and also
the ability of such techniques to preserve the edge
information will be investigated
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