adaptive principal component analysis
Different Viewpoints of Recognizing Fleeting Facial Expressions with DWT
... on adaptive principal component analysis and multilayer perception A proposed scheme of multimodal biometric face and fingerprint recognition is parallel the multimodal biometric takes the ...
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Robust Principal Component Analysis with Adaptive Selection for Tuning Parameters
... of principal component analyzers defined using generic functions which con- tain tuning ...of principal component ...the adaptive selection under three types of outlier distributions H ...
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Neural Network and Adaptive Feature Extraction Technique for Pattern Recognition
... propose adaptive K-means algorithm upon the principal component analysis PCA feature extraction to pattern recognition by using a neural network ...model. Adaptive k-means to ...
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Multi adaptive Natural Language Generation using Principal Component Regression
... combines Principal Com- ponent Analysis (PCA) (Jolliffe, 1986) with lin- ear ...the principal compo- nents, in our case, the factors that contribute the most to the ...these principal ...
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Simultaneous Principal Component Extraction with Application to Adaptive Blind Multiuser Detection
... We have previously studied the performance of the SIPEX-G algorithm and how it compares to several bench- mark algorithms, including Sanger’s rule [7], APEX [2], and LMSER [11], in two previous publications [12, 13]. ...
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Survey of Adaptive Resonance Theory Techniques in IDS
... This paper proposed one hybrid method based on Principal Component Analysis and Fuzzy Adaptive Resonance Theory for identifying various attacks. The evaluation is done on the benchmark data ...
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Development of a graded index microlens based fiber optical trap and its characterization using principal component analysis
... Figure 2. Illustration of the image filtering process and force characterization. (a) shows an original frame from a movie of a 3.00 µm diameter bead trapped with 60mW. (b) shows the same frame as in (a) after the ...
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On Segmentation of Moving Objects by Integrating PCA Method with the Adaptive Background Model
... Tracking and segmentation of moving objects are suffering from many problems including those caused by elimination changes, noise and shadows. A modified algorithm for the adaptive background model is proposed by ...
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Real-time feature extraction of P300 component using adaptive nonlinear principal component analysis
... component from EEG signals in real-time is proposed. The MNN model with back- propagation training algorithm has five layers: the input and output layers have the same number of units N; the first and third layers ...
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Vulnerability of the fishery-based households to the impact of climate change in Rift valley lakes of Ethiopia: Chamo & Hawassa
... score analysis (PCA) To compute the vulnerability index, indicators of adaptive capacity, which are positively associated with the first principal component analysis, and indicators of ...
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Euler principal component analysis
... We evaluate the incremental version of Euler-PCA for the application of visual tracking. The aim of a visual track- ing system is to locate a predefined target object on every frame of a video sequence. Automatic systems ...
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Sources Affecting PM2 5 Concentrations at a Rural Semi Arid Coastal Site in South Texas
... CPF analysis of biomass burns apportioned by PMF2 at CAMS 314 as illustrated in Figure 4 showed similar directional probabilities with major contribution from the northeast and significant levels from south- ...
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Principal Component Analysis of Volatility Smiles and Skews
... The principal component approach that has been developed here allows for non- parallel shifts, which are shown to be particularly important for short maturity ...
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A Review of Constrained Principal Component Analysis (CPCA) with Application on Bootstrap
... regression analysis, where it was considered an important statistical development of the last fifty years, following general linear model (GLM), principal component analysis (PCA) and ...
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Dimensionality Reduction of Image Feature Based on Mean Principal Component Analysis
... proved two theorems: First, the principal diagonal element of the covariance matrix of averaging data is the square of the coefficient of variation of each index. Second, the mean processing of raw data does not ...
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Online Tensor Robust Principal Component Analysis
... In many fields of modern data analysis, the observed data are not necessarily the prime objects of interest. The computer steering a driverless car should pay more attention to objects moving across the foreground ...
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Principal Component Analysis of the Volatility Smiles and Skews
... • Fengler, M., W. Hardle and C. Villa (2000) "The Dynamics of Implied Volatilities: A Common Principal Component Approach" Preliminary version (September 2000) available from ...
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Face Recognition Using Principal Component Analysis
... Face recognition system using the concept of principal component analysis and Genetic Algorithm has been discussed. The simulation is done in MATLAB environment. For implementation this work ...
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Principal Component Analysis with SVM for Disease Diagnosis
... and analysis of a large set of data which holds many intelligence and raw information based on user data, Sensor data, Medical and Enterprise ...Principle Component Analysis (MPCA) is used for ...
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Network Intrusion detection by using PCA via SMO-SVM
... One solution to this is the use of network intrusion detection systems (NIDS), which detect attacks by observing various network activities. It is therefore crucial that such systems are accurate in identifying attacks, ...
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