nonlinear independent component analysis
Improvement of BCI Performance Through Nonlinear Independent Component Analysis Extraction
... a nonlinear independent component analysis (NICA) extraction method entailing time-series EEG signals is ...Discriminant Analysis (FLDA) which has been well developed in the field of ...
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Minimal Nonlinear Distortion Principle for Nonlinear Independent Component Analysis
... the nonlinear independent component analysis (ICA) problem are highly ...“minimal nonlinear distortion” (MND) principle for tackling the ill-posedness of nonlinear ICA ...the ...
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Voltage Flicker Analysis Based on Improved Independent Component Analysis
... increasing nonlinear volatility and impact load in a power system, voltage flicker becomes increasingly serious, and can cause damage to electrical equipment and production ...digital analysis of voltage ...
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A novel fixed point algorithm for constrained independent component analysis
... shows that the c-ncFastICA algorithm performs signifi- cantly better than other two methods. This is due to the fact that ncFastICA does not take the constrained condi- tion into consideration, and symmetric gradient ...
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An Overview of Independent Component Analysis and Its Applications
... Recently, Independent Component Analysis (ICA) has been proposed as a generic statistical model for images [90, 59, 60, 61, 62, ...statistically independent from each other as ...parametric ...
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Leaf vein extraction using independent component analysis
... We also applied the ICA basis functions to several whole leave images and compared the results with the popular edge detection operator, Prewitt operator. Fig. 5 shows two samples of the results. It is noted that the ...
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Characterization of Strombolian events by using independent component analysis
... linear, nonlinear in the regime of limit cycle, and stochastic systems, taking into account both DSs with few and infinite degrees of ...our analysis to li- near/nonlinear systems which are linearly ...
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Nonlinear modal analysis using pattern recognition
... Principal Component Analysis takes a multivariate data set and maps it onto a new set of variables called “principal components”, which are linear combinations of the old ...principal component will ...
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A STUDY OF FACE RECOGNITION TECHNIQUES
... Karhunen-Loeve method is one of the popular methods for feature selection and dimension reduction. Eigen faces are the principal components divide the face into feature vectors. The feature vector information can be ...
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Independent component analysis techniques and their performance evaluation for electroencephalography
... Principal component analysis (PCA) [1.12] is a well known decorrelation technique and has provided another approach for OA removal from the EEG. PCA enables an epoch of multi channel EEG to be decomposed ...
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A Kernel PCA Method for Superior Word Sense Disambiguation
... the nonlinear generalization capability al- lows the data points to be grouped by principal com- ponents reflecting nonlinear patterns in the data dis- tribution, in ways that linear PCA cannot ...
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Face Identification and Recognition System for User Authentication using Advanced Image Processing Techniques
... Principal Component Analysis, Linear Discriminant analysis, Independent Component Analysis) and two transformation techniques (Wavelet Packet Transformation and Curvelet ...
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A Review of Various Linear and Non Linear Dimensionality Reduction Techniques
... The author [8] proposes a novel matrix decomposition technique for large sparse graphs. Several important applications such as research citation network analysis, social network analysis, regulatory ...
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Comparison of Iris Recognition Using Gabor Wavelet, Principal Component Analysis and Independent Component Analysis
... An attempt has been made in this work to compare performance of Iris Recognition based on feature extraction using Gabor wavelet, Principal Component Analysis(PCA) and Independent Component ...
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Electrocardiogram Diagnosis For Arrhythmia Classification Using SVM And ICA
... The highest point of the ECG waveform is R, and the time between consecutive QRS complexes is RR interval. Dynamic nonlinear behavior are observed in the ECG signal during arrhythmia and nonlinear dynamic ...
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Comparative Analysis of Different Feature Extraction Techniques used in Face Recognition – A Review
... Some of the brief surveys on face recognition analysis which uses different feature extraction methods such as PCA, ICA, LBP, LDP were given. Comprehensive survey of different techniques used for face recognition ...
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TEXT INDEPENDENT SPEAKER IDENTIFICATION WITH PRINCIPAL COMPONENT ANALYSIS
... In this paper test independent speaker identification model is developed by using Generalized Gaussian mixture model. The performance of designed model was evaluated with speech database of 40 speakers each with ...
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Advancement Is Independent Component Analysis Speech Enhancement Process
... II. Independent Component Analysis ICA finds the independent components (also called factors, latent variables or sources) by maximizing the statistical independence of the estimated ...
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Performance Analysis of Independent Component Analysis based on Blind Source Separation for extraction of Atrial Activity
... signals analysis the PQRST complex wave of heart ...performance analysis of ECG signal depends upon efficient and accurate detection of QRS wave, and also T and P ...
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Independent component approach to the analysis of EEG and MEG recordings
... Recent research on artifact identification in EEG and MEG recordings, using ICA, has been reported in, e.g., [19], [29], and [31]. Fig. 3 presents a subset of 12 MEG signals, from a total of 122 used in the experiment. ...
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