OBJECTIVE Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) combines advantages of both methods, namely high temporal resolution of EEG and high spatial resolution of fMRI. However, EEG quality is limited due to severe artifacts caused by fMRI scanners. APPROACH To improve EEG data quality substantially, we introduce methods that use a reusable referen...

Learning and adaptation is a fundamental property of intelligent agents. In the context of adaptive information filtering, a filtering agent’s beliefs about a user’s information needs have to be revised regularly with reference to the user’s most current information preferences. This learning and adaptation process is essential for maintaining the agent’s filtering performance. The AGM belief r...

Publish/subscribe system captures the dynamic aspect of the specified information by notifying users of interesting events as soon as possible. Fast response time is important for event filtering which requires multiple step processing and is also one of important factors to provide good service for subscribers. Generally the event arrival rate is time varying and unpredictable. It is very poss...

BACKGROUND As a continuation of our earlier work, we present in this study a Kalman filtering based algorithm for the elimination of motion artifacts present in Near Infrared spectroscopy (NIR) measurements. Functional NIR measurements suffer from head motion especially in real world applications where movement cannot be restricted such as studies involving pilots, children, etc. Since head mov...

In this paper, we propose a novel reduced-rank adaptive filtering algorithm by blending the idea of the Krylov subspace methods with the set-theoretic adaptive filtering framework. Unlike the existing Krylov-subspace-based reduced-rank methods, the proposed algorithm tracks the optimal point in the sense of minimizing the ‘true’ mean square error (MSE) in the Krylov subspace, even when the esti...

Adaptive filtering is used in a wide range of applications including echo cancellation, noise cancellation and equalization. In these applications, the environment in which the adaptive filter operates is often non-stationary. For satisfactory performance under non-stationary conditions, an adaptive filtering is required to follow the statistical variations of the environment. Tracking analysis...

Heart Rate Variability (HRV) is widely used as an index of human autonomic nervous activity. HRV is composed of two major components: high frequency respiratory sinus arrhythmia (RSA) and low frequency sympathetic components. The ratio of LF/HF is viewed as an index of human autonomic balance, so the low frequency sympathetic and the high frequency parasympathetic components of an ECG R-R inter...

The present system of speech enhancement is developing by adaptive filtering approach in digital filters. The adaptive filter utilizes the least mean square algorithm for noise removal, but in practical application of LMS algorithm, a key parameter is the step size. As it is known, if the step size is large, the convergence rate of LMS algorithm will be rapid, but the steady-state mean square e...

Adaptive signal processing theory was born and has lived by exclusively exploiting the mean square error criterion. When we think of the goal of least squares without restrictions of Gaussianity, one has to wonder why an information theoretic error criterion is not utilized instead. After all, the goal of adaptive filtering should be to find the linear projection that best captures the informat...

newspapers and past students' theses. These imaged documents will not be OCR'ed as originally planned due to the overwhelming cost involved. The images are available for public viewing and downloading. The present method will provide an automated means of retrieving similar document images from the library website without having to download every image for inspection of its content to decide it...