This paper exploits independent component analysis (ICA) to obtain transform-based compression schemes adapted to specific image classes. This adaptation results from the data-dependent nature of the ICA bases, learnt from training images. Several coder architectures are evaluated and compared, according to both standard (SNR) and perceptual (picture quality scale – PQS) criteria, on two classe...

We propose a new method to predict time series using the technique of Independent Component Analysis (ICA) as a preprocessing tool. If certain assumptions hold, we show that ICA can be used to transform a set of time series into another set that is easier to predict. These assumptions are not unrealistic for many real-world time series, including financial time series. We have tested this appro...

The electroencephalogram (EEG) signal plays an important role in the detection of epilepsy. The EEG recordings of the ambulatory recording systems generate very lengthy data and the detection of the epileptic activity requires a timeconsuming analysis of the entire length of the EEG data by an expert. The aim of this work is compare the automatic detection of EEG patterns using Discrete wavelet...

Diaphragmatic electromyogram (EMGdi) signal plays an important role in the diagnosis and analysis of respiratory diseases. However, EMGdi recordings are often contaminated by electrocardiographic (ECG) interference, which posing serious obstacle to traditional denoising approaches due to overlapped spectra of these signals. In this paper, a novel method based on wavelet transform and independen...

Introduction: Evoked potentials arisen by stimulating the brain can be utilized as a communication tool  between humans and machines. Most brain-computer interface (BCI) systems use the P300 component,  which is an evoked potential. In this paper, we evaluate the use of the hidden Markov model (HMM) for  detection of P300.  Materials and Methods: The wavelet transforms, wavelet-enhanced indepen...

This paper proposes three approaches to content-based watermarking for image authentication based on Independent Component Analysis (ICA). In this scheme, ICA is applied to blocks of the cover image and the resulting mixing matrix is used as the content-based feature. This is embedded in the mid-frequency DCT coefficient of the block in the first method. The watermark is embedded in the 3 rd le...

This paper describes a comparative analysis of recognition accuracy using feature extraction algorithm. A feature extraction algorithm is introduced for face recognition, Principle Component Analysis (PCA),Linear Discriminant Analysis(LDA) , Independent Component Analysis(ICA) and Nonnegative matrix factorization (NMF) based on curvelet transform. Mostly recognition system is capable to perform...

This paper explores the utility of the Independent Component Analysis (ICA) for remote sensing applications and compares it directly to the Principal Component Transform (PCT). The ICA is a signal processing method that extracts independent signal sources from a composite signal. It has been applied to a wide area of applications ranging from electroencephalography, for understanding brain acti...

[1] Seasonal forecasting of streamflow provides many benefits to society, by improving our ability to plan and adapt to changing water supplies. A common approach to developing these forecasts is to use statistical methods that link a set of predictors representing climate state as it relates to historical streamflow, and then using this model to project streamflow one or more seasons in advanc...