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A new wavelet packet image compression method is proposed based on PSO algorithm. The PSO is utilized to find out the best wavelet packet basis for image compression. A fitness function is designed in terms of the Mean Square Error (MSE) and the sum of the node entropy. Compared with the global soft threshold compression algorithm provided by Matlab soft, the proposed method exhibits better compression...
A new hybrid algorithm (WPNOSC-NPLS) is proposed to eliminate the interference of temperature variation and develop the robust calibration models for determining the main components concentration in milk using the near infrared spectra. At first, the three dimensional (3D) spectra including wavelength, temperature and absorbency are constructed. Through unfolding method, the wavelet packet transform...
To take advantages of multiscale property of near infrared (NIR) spectra, a new hybrid algorithm (GA-WPLS) was proposed for developing the multivariate regression model in the wavelet domain instead of the spectra domain. At first, wavelet packet transform (WPT) algorithm and its reconstruction algorithm are employed to split the raw spectra into different frequency components in wavelet domain. Then...
This paper aims to explore a method about electrocardiogram (ECG) signal denoising based on Hilbert-Huang Transform. The empirical mode decomposition method can decompose the noisy signal into a number of Intrinsic Mode Functions. Energy analysis is conducted on the IMFs to find out the boundary between the noise-dominated IMFs and ECG signal dominated IMFs accurately. The most noisy IMFs are denoised...
A new algorithm (WFCE) was proposed for simultaneously eliminating background and noise based on wavelet packet transform (WPT) and information entropy theory. At first, WPT algorithm and reconstruction algorithm were employed to split the raw spectra into different frequency components. Then the information entropy of each frequency component was calculated, showing the uncertainty to the measured...
A new hybrid algorithm (EWPCS) was proposed for selecting appropriate wavelet packet components containing the variations of analyte as the input data of regression model based on wavelet packet transform (WPT) and information entropy theory. At first, WPT algorithm and its reconstruction algorithm are employed to split the raw spectra into different frequency components with the maximum levels. Then...
Knowledge discovery from time series may help us better recognize the revolving regularity of the system. The state-of-art feature extraction methods from time series are single-scale methods that result in imprecision of the feature location and inferior quality of the discovered pattern. A novelty multiscale feature extraction method from time series is proposed based on the principle of wavelet...
On the basis of introducing and discussing the wavelet decomposition, principal component analysis and support vector machine, an approach to face recognition is proposed in this paper. Firstly, wavelet decomposition is used to reduce facial image dimension. Secondly, under the premise of not increasing the number of images, symmetric principal component analysis is employed to expand the sample size...
For the purpose of fault diagnosis of power transformers, an approach using genetic wavelet networks (GWNs) is proposed in this paper. The GWNs have a three-layer structure which contains wavelet, weighting and summing layers. By genetic algorithm (GA), the GWNs tune the network parameters, translation and dilation in the wavelet nodes and the weighting values in the weighting nodes automatically...
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