Saccades are conjunctive and believed to be the fastest eye movements, which function to redirect the fovea of the retina to the object of interest. Main sequence relations have generally been used for describing the dynamics of the saccadic eye movements. Fourier analysis has also been used in quantitative investigation of saccades. A previous investigation used an inverse method from the Four...

This paper examines the applicability of some learning techniques to the classification of phonemes. The methods tested were artificial neural nets (ANN), support vector machines (SVM) and Gaussian mixture modeling. We compare these methods with a traditional hidden Markov phoneme model (HMM) working with the linear prediction-based cepstral coefficient features (LPCC). We also tried to combine...

We use principal component analysis (PCA) to identify exons of a gene and further analyze their internal structures. The PCA is conducted on the short-time Fourier transform (STFT) based on the 64 codon sequences and the 4 nucleotide sequences. By comparing to independent component analysis (ICA), we can differentiate between the exon and intron regions, and how they are correlated in terms of ...

The increasingly popular independent component analysis (ICA) may only be applied to data following the generative ICA model in order to guarantee algorithmindependent and theoretically valid results. Subspace ICA models generalize the assumption of component independence to independence between groups of components. They are attractive candidates for dimensionality reduction methods, however a...

Independent component analysis (ICA), instead of the traditional discrete cosine transform (DCT), is often used to project log Mel spectrum in robust speech feature extraction. The paper proposed using symmetric orthogonalization in ICA for projecting log Mel spectrum into a new feature space as a substitute in extracting speech features to solve the problem of cumulative error and unequal weig...

Blind Source Separation (BSS) refers to the process of recovering source signals from a given mixture of unknown source signals were in no prior information about source and mixing methodology is known. Independent Component Analysis (ICA) is widely used BSS technique which allows separation of source components from complex mixture of signals based on certain statistical assumptions. This pape...

In this paper, human face recognition of still images has been proposed. The proposed system involves five steps: face detection by AdaBoost face detector, region of interest (ROI) extraction, feature extraction using discrete wavelet transform (DWT), dimensionality reduction by employing independent component analysis (ICA) and classification using k-Nearest Neighborhood (k-NN) classifier. Exp...

We present a method for transforming neutral visual speech sequences into realistic expressive visual speech sequences. By applying Independent Component Analysis (ICA) to visual features extracted from time aligned neutral and equivalent expressive sequences, a model that separates speech from expression can be learned. Analyzing the behavior of different speaking styles in terms of this model...

Electroencephalogram (EEG) signals are having very small amplitudes and because of that they can be easily contaminated by different Artifacts. The presence of artifacts makes the analysis of EEG difficult for clinical evaluation. The major types of artifacts that affect the EEG are Power Line noise, eye movements, Electromyogram (EMG), and Electrocardiogram (ECG). Out of these artifacts Power ...