In quantitative electroencephalography, it is of vital importance to eliminate non-neural components, as these can lead an erroneous analysis the acquired signals, limiting their use in diagnosis and other clinical applications. light this drawback, preprocessing pipelines based on joint Wavelet Transform Independent Component Analysis technique (wICA) were proposed 2000s. Recently, with advent...

Icariin (ICA) is a major component isolated from Epimedium brevicornum. Emerging evidence shows that ICA can inhibit tumor cell proliferation, invasion and migration. However, the anti-cancer effect of ICA on B16 cells has not been fully investigated. Here we found that the proliferation of B16 cells was inhibited by ICA in a concentration- and time-dependent manner, and the colony formation of...

Icariin (ICA), the main active flavonoid glucoside isolated from Herba Epimedii, has been shown to prevent postmenopausal bone loss in vitro. However, the mechanisms by which ICA prevents bone loss in vivo remain poorly understood. In the present study, the effect of ICA in an ovariectomized (OVX) rat model of osteoporosis was evaluated. Sprague-Dawley rats were divided into sham-operated and O...

In this paper, we address the problem of blind separation of speech mixtures. We propose a new blind speech separation system, which integrates a perceptual filterbank and independent component analysis (ICA) and using kurtosis criterion. The perceptual filterbank was designed by adjusting undecimated wavelet packet decomposition (UWPD) tree in order to accord to critical band characteristics o...

The Severe Acute Respiratory Syndrome (SARS) are caused by the strain of corona virus causes cold and influenza. In recent years, covid pandemic spread throughout world killing millions people. fatality rate has increased it also leads to pneumonia for breathing problems. Several methods like wavelet filter banks, time series methods, Neural networks was developed diagnosis severe acute respira...

Ocular artifact (OA) is one of the main interferences in electroencephalogram (EEG) recordings. It appears as a big pulse and has a strong impact to EEG signals. To overcome OA interference in EEG data, a novel automatic method of OA removal, denoted as DWICA, was proposed in this paper. In DWICA, the discrete wavelet transform (DWT) is applied to every recorded signal to obtain multiple scale ...

The study adresses the problem of spectral unmixing hyperspectral images, technique allowing the spectra and abundance of each pure material present in each pixel of a scene to be extracted. We first remark that the linear model commonly used in spectral unmixing is exactly the same as the model used in the Independant Component Analysis (ICA), a blind source separation technique studied in the...

This paper proposes a new approach to watermarking multimedia products by redundant discrete wavelet transform (RDWT) and independent component analysis (ICA). For watermark security, embedded logo watermarks are encrypted to random noise signal. To embed logo watermarks, the original image is decomposed by RDWT, and watermarks are embedded into middle frequency at LH and HL sub-bands. The perc...

This paper addresses the problem of blind source separation in the situation where the mixing process is dynamic. We first present a new ICA algorithm for the static mixing problem that exploits a wavelet representation of the signals. This outperforms standard ICA in our experiments thus allowing the unmixing to be estimated from a smaller number of samples. We use this to create a sliding win...

recent studies on wavelet transform and fractal modeling applied on mammograms for the detection of cancerous tissues indicate that microcalcifications and masses can be utilized for the study of the morphology and diagnosis of cancerous cases. it is shown that the use of fractal modeling, as applied to a given image, can clearly discern cancerous zones from noncancerous areas. in this paper, f...