Shun Chi Wu

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Source signals that have strong temporal correlation can pose a challenge for high-resolution EEG source localization algorithms. In this paper, we present two methods that are able to accurately locate highly correlated sources in situations where other high-resolution methods such as multiple signal classification and linearly constrained minimum variance(More)
Suppression of strong, spatially correlated background interference is a challenge associated with electroencephalography (EEG) source localization problems. The most common way of dealing with such interference is through the use of a prewhitening transformation based on an estimate of the covariance of the interference plus noise. This approach is based(More)
In this paper, we propose novel matching pursuit (MP)-based algorithms for EEG/MEG dipole source localization and parameter estimation for multiple measurement vectors with constant sparsity. The algorithms combine the ideas of MP for sparse signal recovery and source deflation, as employed in estimation via alternating projections. The source-deflated(More)
An interference suppression algorithm is proposed for canceling the spatially correlated background noise and interference in EEG/MEG source localization applications. Rather than using the standard prewhitening approach, the proposed algorithm attempts to directly null interference using a projection operator obtained from a set of secondary, control-state(More)
Multi-sensor electrodes for extracellular recording of neuronal action potentials have significantly increased the signal-to-noise ratio (SNR) in neurophysiological experiments, ultimately leading to a more accurate interpretation of scientific data. Apart from improving SNR, we hypothesize that these electrodes can be used to estimate the location of(More)
A matching pursuit (MP) based algorithm, called source deflated matching pursuit (SDMP), is proposed for locating sources of brain activity. By iteratively deflating the contribution of identified sources to multiple measurement vectors (MMVs), the SDMP algorithm transforms the original multi-basis-vector/matrix selection problem into a(More)
This article presents a new technology for satellite orbit determination using a simple Global Positioning System (GPS) receiver (microGPS) with ultra-low cost, power, and mass. The capability of low-cost orbit determination with mi-croGPS for a low Earth-orbiting satellite, Student Nitric Oxide Explorer (SNOE), is demonstrated using actual GPS data from(More)
Recent advances in neurophysiology have led to the development of complex dynamical models that describe the connections and causal interactions between different regions of the brain. These models are able to accurately mimic the event-related potentials observed by EEG/MEG measurement systems, and are considered to be key components for understanding(More)
This paper proposes a novel matched subspace detector (MSD) based algorithm for extracting discriminant features from multi-sensor measurements of extracellular action potentials (APs) to facilitate their subsequent separation according to the neuron of origin. The method does not require the construction of AP templates, and is therefore suitable for(More)