Functional Magnetic Resonance Imaging inherently involves noisy measurements and a severe multiple test problem. Smoothing is usually used to reduce the effective number of multiple comparisons and to locally integrate the signal and hence increase the signal-to-noise ratio. Here, we provide a new structural adaptive segmentation algorithm (AS) that naturally combines the signal detection with ...

Data from functional magnetic resonance imaging (fMRI) consist of time series of brain images that are characterized by a low signal-to-noise ratio. In order to reduce noise and to improve signal detection, the fMRI data are spatially smoothed. However, the common application of a Gaussian filter does this at the cost of loss of information on spatial extent and shape of the activation area. We...

 A step-by-step algorithm for enhancement of periodic signals that are highly corrupted by additive uncorrelated white gausian noise is proposed. In each adaptation step a new parallel second-order section is added to the previous filters. Every section has only one adjustable parameter, i.e., the center frequency of the self-tuning filter. The bandwidth and the convergence factor of each secti...

Underwater acoustic communication systems suffer from the channel impairments which results in time spreading of the transmitted signal. In underwater environment, multiple replicas of the transmitted signal are received at the receiver through different paths, which causes significant Inter-Symbol Interference (ISI). Decision Feedback Equalizers (DFE) was utilized to overcome this type of inte...

In this paper we propose a new cooperative spectrum sensing method using adaptive double threshold energy and matched filter detector in cognitive radio networks. The energy detector (ED) performance is highly degraded under noise uncertainty condition. Also, ED cannot well differentiate between the signal and noise, if the detected observational value of the primary user (PU) lies in the confu...

This paper proposes an oblivious watermarking algorithm with blind detection approach for high volume data hiding in image signals. We present a detection reliable signal adaptive embedding scheme for multiple messages in selective sub-bands of wavelet (DWT) coefficients using direct sequence spread spectrum (DS-SS) modulation technique. Here the impact of volumetric distortion sources is analy...

In this paper , the use of adaptive weights over the radar measurement dimensions of pulse time, antenna receive element, and wideband frequency is extended to cover a much broader range of radar detection problems than was supposed in the original formulation of spacetime adaptive signal processing (STAP). These problems include, among others (1) Adaptive beamforming in three dimensions; (2) D...

In order to improve the optimal performance of a machining process, a booster to improve the serve control system performance with high stability for EDM is needed. According to precise movement of machining process using electrical discharge (EMD), adaptive control is proposed as a major option for accuracy and performance improvement. This article is done to design adaptive controller based o...

This paper introduces a novel approach to novelty detection of every individual sample of data in a time series. The novelty detection is based on the knowledge learned by neural networks and the consistency of data with contemporary governing law. In particular, the relationship of prediction error with the adaptive weight increments by gradient decent is shown, as the modification of the rece...