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In this paper, we propose a method for decomposing speech signals, evaluating the discriminative, and determining the representative vectors of signal sets. At first, we decompose all speech signals with the level four Db4 wavelet decomposition to reconstruct the approximation sub-signals of all four levels, transfer all the speech signals and the sub-signals into the Linear Prediction Codes (LPC),...
In recent years, geophysical approaches are being commonly used in modeling and pre-processing of excavation of buried archeological structures. The methods to be applied for the archeological structures are decided due to the comments of the archeologists. Thus more information about the place and the type of the structure of the archaeological ruins can be obtained. Thus only the area that archaeological...
Retinal image enhancement techniques have a vital role in retinal decease identification, enhanced features ease the identification of optic disc and the edges of the retinal image. In this approach input images are taken from the STARE data base and separating the high frequency components using wavelet filtering and performing edge sharpening and constructing back using wavelet reconstruction and...
Remote sensing technologies are very useful due to their wide practical applications. The latest new technology, hyperspectral imaging, could be a valuable tool to study and evaluate many economic and environmental issues. It offers an advanced monitoring technique in more detailed spectral information than previous remote sensing systems. The present work is devoted to the study of segmentation of...
The THz image has lower contrast and bigger noise because the THz radiant power is small, so a multi-scales nonlinear enhancement method of THz image is proposed for the purpose of improving the image definition. The THz image is decomposed into multi-scales detail coefficients and approximation coefficients by utilizing the wavelet transform. The detail coefficients are taken to denoise and histogram...
In this paper the possibility of SpO2 signal preprocessing is studied and the influence of signal smoothing on the alarm level and duration is investigated. Dyadic wavelet transform was applied to SpO2 signal and the reconstruction for different levels using approximation part was performed, considering the time duration of wavelet and scaling functions. 68 signals from PhysioNet MIMIC II database...
The goal of this study was to analyze whether schizophrenia patients may exhibit distinctive sub-band EEG features from control subjects compared both at rest and during auditory stimulation periods. EEG signals of thirty schizophrenic patients and age-gender matched healthy subjects were recorded from F3 left frontal region and analyzed using wavelet decomposition and Welch power spectral density...
LQ45 is a stock market index for Indonesia Stock Exchange (ISX) consists of 45 companies that fulfill certain criteria to aim investor choosing some stocks. However, whether these stocks have tended to rise in price within a specified period. In this paper we analyze some stocks in LQ45 by discrete wavelet transforms. We decomposed signals from closed prices by discrete wavelet transform. Approximation...
We present a new type of the EnKF for data assimilation in spatial models that uses diagonal approximation of the state covariance in the wavelet space to achieve adaptive localization. The efficiency of the new method is demonstrated on an example.
In this paper, a new algorithm for ECG waves segmentation is described. The algorithm is based on the wavelet transform for the complex QRS delineation and a surface indicator for the detection of the T-end waves. The described algorithm was evaluated using ECG signals from the universal database MIT BIH. A sensitivity of 99.35% and a positive predictivity of 99.05% are reached. Those obtained results...
The quality of magnetic resonance images (MRI) is often limited by anisotropic voxels necessitated by acquisition considerations. Examination of the 3D anatomy and post-processing of such images is challenged by the partial volume effects due to such anisotropic voxels. We propose a method based on the separable wavelet transform to fuse anisotropic clinical images, which are often acquired in perpendicular...
Gait analysis using wireless accelerometers deployed as body area networks can provide valuable information for multiple health-related applications. Within this field, stride length estimation represents a difficult task. In this paper we present a novel method to estimate stride length through the application of the wavelet transform to the signal obtained from a wireless accelerometer on the waist...
A multi-resolution path planning algorithm based on the wavelet transform of the environment has been reported previously in the literature. In this paper, we provide a proof of completeness of this algorithm. In addition, we present an implementation of this algorithm that reuses information obtained in previous iterations to perform subsequent iterations more efficiently. Finally, we extend this...
With the increasing growth of technology and the entrance into the digital age, we have to handle a vast amount of information every time which often presents difficulties. So, the digital information must be stored and retrieved in an efficient and effective manner, in order for it to be put to practical use. Wavelet Transform has been proved to be a very useful tool for image processing in recent...
Correspondence estimation in one of the most active research areas in the field of computer vision and number of techniques has been proposed, possessing both advantages and shortcomings. Among the techniques reported, multiresolution analysis based stereo correspondence estimation has gained lot of research focus in recent years. Although, the most widely employed medium for multiresolution analysis...
This paper presents a wavelet-based method for real-time detection of voltage sags in transmission lines. The wavelet coefficient energies of the phase voltages and currents are used for real-time detection of the transients at both beginning and end times of voltage sags. On the other hand, the voltage sags are identified in real-time by means of the approximation coefficient energy analysis. The...
This paper describes a Wavelet Transform and Rule-Based method for detection and classification of various events of power quality disturbances. In this model, wavelet Multi-Resolution Analysis (MRA) technique was used to decompose the signal into its various details and approximation signals, and unique features from the 1st, 4th, 7th and 8th level detail are obtained as criteria for classifying...
Wavelet-based techniques for fault detection usually employ one of two basic approaches, namely (a) decomposition of a measured signal containing fault-related information or (b) decomposition of a residue calculated as the difference between sensor readings and the output of a model. An alternative approach, which was recently proposed in, consists of employing the wavelet transform to identify a...
A new images denoising method based on nonuniform partition approximation and wavelet transform is proposed. The key point of non-uniform partition approximation is that the gray values of the pixels are regarded as fitting data, which is fitted with the least squares method, and then the digital image is expressed as a piecewise polynomial. The nonuniform partition approximation can realize image...
The main problem that watershed image segmentation facing is over segmentation. The paper that combines adaptive threshold decision and watersheds improves the traditional image segmentation technology. Firstly, applying the wavelet transform to get the detail and approximation information. Based on the gradient magnitudes of the approximation image at the coarsest resolution, an adaptive threshold...
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