Partitioned Factor Analysis for Interference Suppression and Source Extraction
نویسندگان
چکیده
It is common for data to be contaminated with artifacts, interference, and noise. Several methods including independent components analysis (ICA) and principal components analysis (PCA) have been used to supress these undesired signals and/or to extract the underlying (desired) source waveforms. For some data it is known, or can be extracted posthoc, how to partition the data into periods of source activity and source inactivity. Two examples include cardiac data and data collected using the stimulus-evoked paradigm. However, neither ICA nor PCA are able to take full advantage of the knowledge of the partition. Here we introduce an interference supression method, partitioned factor analysis (PFA), that takes into account the data partition.
منابع مشابه
Neuropsychological Decomposing Stroop Interference Into Different Cognitive Monitoring; An Exploratory Factor Analysis
Introduction: There are two alternative explanations of the Stroop phenomenon. Several studies have revealed that the difference in performance on congruent and incongruent trials can arise from response interference. On the contrary, many authors have claimed that Stroop interference might occur at earlier processing stages related to semantic or conceptual encoding. The present study aims to ...
متن کاملProbabilistic algorithms for MEG/EEG source reconstruction using temporal basis functions learned from data
We present two related probabilistic methods for neural source reconstruction from MEG/EEG data that reduce effects of interference, noise, and correlated sources. Both methods localize source activity using a linear mixture of temporal basis functions (TBFs) learned from the data. In contrast to existing methods that use predetermined TBFs, we compute TBFs from data using a graphical factor an...
متن کاملSemi-blind Interference Suppression on Coherent Multipath Environments
Blind source separation (BSS) can be used to separate an interfering source from a set of desired signals. By exploiting the statistical independence between the source signals and the interference, we present an alternative to the blind beamformer for suppressing the interference. [1, 2] presented the concept of combining Independent Component Analysis (ICA) with a conventional detection for s...
متن کاملA Protocol for Pollution Index, Source Identification, and Spatial Analysis of Heavy Metals in Top Soil
Introduction: This study aimed to assess a good protocol for the contamination indexes, concentration, spatial analysis, and source identification of toxic metals in top soils. Materials and Methods: In the first step, samples were taken from top soil (30 cm) and the metals were extracted and detected with ICP-AES. In the second step, Enrichment Factor, Geoaccumulation Index, and Contamination...
متن کاملOptimum conditions for protein extraction from tuna processing by-products using isoelectric solubilization and precipitation processes
The by-product from tuna processing is a potential source of edible protein. Therefore, it is very important to extract protein from such raw materials for human food. In this study the optimum pH for protein extraction from tuna by-products was optimized by using isoelectric solubilization and precipitation processes. The Response Surface Methodology (RSM) and the single factor model were used...
متن کامل