In recent years, access to multimedia data has become much easier due to rapid growth of the internet. While this is usually considered an improvement of everyday life, it also makes unauthorized copying and distributing of multimedia data much easier, therefore presenting a field of watermarking.Many literatures have reported about Discrete Wavelet Transform (DWT) based watermarking for data s...

This study aims at proposing an efficient method for automated electrocardiography (ECG) artifact removal from surface electromyography (EMG) signals recorded from upper trunk muscles. Wavelet transform is applied to the simulated data set of corrupted surface EMG signals to create multidimensional signal. Afterward, independent component analysis (ICA) is used to separate ECG artifact componen...

In this paper we address the orthogonalization of independent component analysis (ICA) to obtain transform-based image coders. We consider several classes of training images, from which we extract the independent components, followed by orthogonalization, obtaining bases for image coding. Experimental tests show the generalization ability of ICA of natural images, and the adaptation ability to ...

View NONINVASIVE IMAGING OF INDEPENDENT CORTICAL FLOW PATTERNS. While independent component analysis (ICA) is useful for modeling brain and electroencephalographic (EEG) data, current ICA methods for EEG model signal sources as acting in perfect synchrony within spatially fixed domains. In contrast, invasive animal recordings have observed waves of neuronal activity propagating quickly across m...

Harold Szu, FELLOW SPIE Office of Naval Research Arlington, Virginia 22217 Abstract. We investigate the application of independent-component analysis ICA to remotely sensed hyperspectral image classification. We focus on the performance of two well-known and frequently used ICA algorithms: joint approximate diagonalization of eigenmatrices JADE and FastICA; but the proposed method is applicable...

We examine various independent component analysis (ICA) digital signal processing algorithms for estimating the arterial oxygen saturation (SpO2) as measured by a reflective pulse oximeter. The ICA algorithms examined are FastICA, Maximum Likelihood ICA (ICAML), Molgedey and Schuster ICA (ICAMS), and Mean Field ICA (ICAMF). The signal processing includes pre-processing bandpass filtering to eli...

Independent component analysis (ICA) is a computational mehtod to solve blind source separation (BSS) problem. Different kinds of classic measure can be used for the estimation of nonGaussian sources by ICA. In this paper we review independent componenet analysis (ICA) technique based on Kurtosis contrast function. We briefly present the common independent component analysis algorithms that use...

microarray data have an important role in identification and classification of the cancer tissues. having a few samples of microarrays in cancer researches is always one of the most concerns which lead to some problems in designing the classifiers. for this matter, preprocessing gene selection techniques should be utilized before classification to remove the noninformative genes from the microa...

In recent years, watermarking has become an attractive field in areas like copyright protection, image authentication and biomedical engineering. Many literatures have reported about discrete wavelet transform (DWT) watermarking techniques for data security. However, DWT based watermarking schemes are found to be less robust against image processing attacks. In this paper, an attempt is made to...

In this paper we propose an information theory based generic method for complex Independent Component Analysis (ICA). Expressions for the complex score function are derived. The method exploits the full second order structure of complex signals. It combines a preprocessing step called the strong−uncorrelating transform (SUT) with ICA methods that use the proposed complex score function. The met...