The sinusoidal model has proven useful for representation and modi cation of speech and audio. One drawback, however, is that a sinusoidal signal model is typically derived using a xed frame size, which corresponds to a rigid signal segmentation. For nonstationary signals, the resolution limitations that result from this rigidity lead to reconstruction artifacts. It is shown in this paper that ...

electrocardiogram (ecg) is one of the most common biological signals which plays a significant role in diagnosis of heart diseases. one of the most important parts of ecg signal processing is interpretation of qrs complex and obtaining its characteristics. r wave is one of the most important sections of this complex which has an essential role in diagnosis of heart rhythm irregularities and als...

In many signal processing applications, such as EEG analysis, the non-stationary signal is often required to be segmented into small epochs. This is accomplished by drawing the boundaries of signal at time instances where its statistical characteristics, such as amplitude and/or frequency, change. In the proposed method, the original signal is initially decomposed into signals with different fr...

We use Bayesian methods to design cellular neural networks for signal processing tasks and the Boltzmann Machine learning rule for parameter estimation. The learning rule can be used for models with uhidden" units, or for compietely unsupervised learning. The latter is exemplified by unsupervised adaptation of an image segmentation cellular network, in particular we apply the learning rule to a...

Compared with thresholding methods based on the traditional wavelet transform (WT), empirical (EWT) has been demonstrated to outperform in terms of noise elimination by constructing an adaptive filter bank. However, as state-of-the-art version EWT, enhanced EWT (EEWT) requires that number components superposed signal prior knowledge is known, which impractical reality and limits application thi...

Adaptive frequency band (AFB) and ultra-wide-band (UWB) systems require either rapidly changing or very high sampling rates. Conventional analog-to-digital devices have non-adaptive and limited dynamic range. We investigate AFB and UWB sampling via a basis projection method. The method decomposes the signal into a basis over time segments via a continuous-time inner product operation and then s...

Optical aberrations deteriorate the performance of microscopes. Adaptive optics can be used to improve imaging performance via wavefront shaping. Here, we demonstrate a pupil-segmentation based adaptive optical approach with full-pupil illumination. When implemented in a two-photon fluorescence microscope, it recovers diffraction-limited performance and improves imaging signal and resolution.

In recent years, active filters have been considered and developed for elimation of harmonics in power networks. Comparing with passive, they are smaller and have better compensating characteristics and resistance to line distortions. In this paper, a novel idea based on adaptive filter theory in presented to develop an active filter to eliminate the distortions of an arbitrary signal. Using th...