This paper compares the correlation dimension (D2) ,Higuchi fractal dimension (HFD),Katz fractal dimension(KFD)and Sevcik fractal dimension(SFD) approaches in estimating Depth of Anesthesia (DOA) based on of electroencephalogram (EEG). The single-channel EEG data was captured in both ICU and operating room and different anesthetic drugs, including propofol and isoflurane were used. For better a...

Various segmentation algorithms have been proposed for better classification of the highly nonstationary heart sounds. This paper proposes an improved segmentation technique based on Shannon Energy calculation of the phonocardiogram using adaptive windows. The major focus of the research has been on a simple yet comprehensive signal representation as well as on extracting most information from ...

the record of human brain neural activities, namely electroencephalogram (eeg), is generally known as a non-stationary and nonlinear signal. in many applications, it is useful to divide the eegs into segments within which the signals can be considered stationary. combination of empirical mode decomposition (emd) and hilbert transform, called hilbert-huang transform (hht), is a new and powerful ...

The paper describes and compares two time domain algorithms for segmenting voiced speech into quasiperiodical units that correspond to pitch periods. The first algorithm uses the similarity of adjacent segments to build a graph that represents distances between them and finds the minimal path in it using a "greedy" algorithm. The second algorithm implements a set of heuristics that imitate acti...

Although traditional signal-based structural health monitoring algorithms have been successfully employed for small structures, their application for large and complex bridges has been challenging due to non-stationary signal characteristics with a high level of noise. In this paper, a promising damage detection algorithm is proposed by incorporation of adaptive signal processing and Artificial...

Speech segmentation is an essential stage in designing automatic speech recognition systems and one can find several algorithms proposed in the literature. It is a difficult problem, as speech is immensely variable. The aim of the authors’ studies was to design an algorithm that could be employed at the stage of automatic speech recognition. This would make it possible to avoid some problems re...

Potato image segmentation is an important part of image-based potato defect detection. This paper presents a robust potato color image segmentation through a combination of a fuzzy rule based system, an image thresholding based on Genetic Algorithm (GA) optimization and morphological operators. The proposed potato color image segmentation is robust against variation of background, distance and ...

in this paper, we propose a technique of artificial intelligence called adaptive neuro fuzzy inference system (anfis) for canceling maternal electrocardiogram (mecg) in fetal electrocardiogram extraction (fecg).this technique is used to estimate the mecg present in the abdominal signal of a pregnant woman. the fecg is then extracted by subtracting the estimated mecg from the abdominal signal. p...

one of the common problems in reflection seismic records in the land is the existence of surface waves with high amplitude and low frequency which cause the most important parts of reflective signals to be masked. therefore, it is necessary to attenuate them by processing and acquisition methods. as it is impossible to attenuate the surface waves completely, and sometimes it is likely to damage...

Best-basis searching algorithm based on binary (in general, M-ary) segmentation was constructed by Coifman and Wickerhauser in 1992 [1] (IEEE Trans. on Information Theory, 38, 713-718). However, there are several problems with the binary scheme. First, the binary segmentation is inflexible in grouping signals along the axis. Secondly, the binary-based segmentation method is very sensitive to ti...