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Canonical correlation analysis (CCA) is applied to analyze the frequency components of steady-state visual evoked potentials (SSVEP) in electroencephalogram (EEG). The essence of this method is to extract a narrowband frequency component of SSVEP in EEG. A recognition approach is proposed based on the extracted frequency features for an SSVEP-based brain(More)
As the number of electrodes increases, topographic scalp mapping methods for electroencephalogram (EEG) data analysis are becoming important. Canonical correlation analysis (CCA) is a method of extracting similarity between two data sets. This paper presents an EEG topographic scalp mapping -based CCA for the steady-state visual evoked potentials (SSVEP)(More)
Different types of sensors are being used to study deglutition and mastication. These often suffer from problems related to portability, cost, reliability, comfort etc. that make it difficult to use for long term studies. An inertial measurement based sensor seems a good fit in this application; however its use has not been explored much for the specific(More)
Along with the development of information technology, business intelligence plays an important role in the bank operation process. Bank Intelligence is a method of storing and presenting key bank business data so that anyone in the bank can quickly and easily ask questions of accurate and timely data. In a bank network, hundreds of millions of customer data(More)
We present an innovative approach for clustering retail customers using semi-supervised geographic information. The approach aims at clustering (or segmenting) customers not only depending on their age, spending, etc., but also on their dwelling, which can discover useful customer patterns for the retailer's marketing strategy. In real retail applications,(More)
Canonical Correlation Analysis (CCA) is used to frequency recognition of multichannel signals. The unknown signals are compared against known templates and their frequencies are recognized by simply comparing the biggest coefficients of their CCA coefficient vectors. This strategy is straightforward but may not give optimal results. To boost the accuracy of(More)