Canonical Correlation Analysis Technique Research Articles

An Application of Canonical Correlation Analysis Technique to Land Cover Classification of LANDSAT Images

This research is an attempt to obtain more accurate land cover information from LANDSAT images. Canonical correlation analysis, which has not been widely used in the image classification community, was applied to the classification of a LANDSAT image. It was found that it is easy to select training areas on the classification using canonical correlation analysis in comparison with the maximum likelihood classifier of ERDAS® software. In other words, the selected positions of training areas hardly affect the classification results using canonical correlation analysis. When the same training areas are used, the mapping accuracy of the canonical correlation classification results compared with the ground truth data is not lower than that of the maximum likelihood classifier. The kappa analysis for the canonical correlation classifier and the maximum likelihood classifier showed that the two methods are alike in classification accuracy. However, the canonical correlation classifier has better points than the maximum likelihood classifier in classification characteristics. Therefore, the classification using canonical correlation analysis applied in this research is effective for the extraction of land cover information from LANDSAT images and will be able to be put to practical use.

A statistical methodology for deriving reservoir properties from seismic data

The use of seismic data to better constrain the reservoir model between wells has become an important goal for seismic interpretation. We propose a methodology for deriving soft geologic information from seismic data and discuss its application through a case study in offshore Congo. The methodology combines seismic facies analysis and statistical calibration techniques applied to seismic attributes characterizing the traces at the reservoir level. We built statistical relationships between seismic attributes and reservoir properties from a calibration population consisting of wells and their adjacent traces. The correlation studies are based on the canonical correlation analysis technique, while the statistical model comes from a multivariate regression between the canonical seismic variables and the reservoir properties, whenever they are predictable. In the case study, we predicted estimates and associated uncertainties on the lithofacies thicknesses cumulated over the reservoir interval from the seismic information. We carried out a seismic facies identification and compared the geological prediction results in the cases of a calibration on the whole data set and a calibration done independently on the traces (and wells) related to each seismic facies. The later approach produces a significant improvement in the geological estimation from the seismic information, mainly because the large scale geological variations (and associated seismic ones) over the field can be accounted for.

User characteristics—DSS effectiveness linkage: an empirical assessment

Despite extensive research on various factors affecting the acceptance and effectiveness of decision support systems (DSS), considerable ambiguity still exists regarding the role and influence of user characteristics. Although researchers have advocated DSS effectiveness as a multi-dimensional construct, specific guidelines regarding its dimensions or the approach to derive it is lacking. The study reported here attempts to contribute to the existing body of knowledge by proposing a multi-dimensional construct for DSS effectiveness and identifying a comprehensive set of user characteristics that influences DSS effectiveness. It critically examines the relationship between these two sets through canonical correlation analysis technique. Thirty seven students, taking a graduate level course in financial management, in a large university located in the north eastern part of the United States participated in the study acting as surrogates for real-world managers. The results of the study highlight that user's domain-related expertise, system experience, gender, intelligence, and cognitive style have important influence on one or more dimensions of DSS effectiveness. However, their relative importance vary with the outcome measure of choice.

Predictability Between Objective Physical Factors of Fabrics and Subjective Preference Votes for Derived Garments

The relationships have been investigated between subjective preference votes, collected under three different conditions, for garments derived from a range of fabric materials and objective physical factors (where “factors” are grouped properties) measured for the same materials. The technique of canonical correlation analysis was applied, and three canonical correlations between subjective preference votes and objective physical factors were found to be highly significant (P 0.950). Canonical redundancy analysis showed that the objective physical factors of fabrics had great predictive power for the subjective votes, with cumulative redundancy over 0.983. The subjective preference votes, however, were poor predictors for the physical factors of fabrics, with cumulative redundancy only 0.467. The squared multiple correlations suggested that the first three canonical variables of the objective factors of fabrics had very good predictive power for all three subjective preference votes, but the...

Adaptation of automatic speech recognizers to new speakers using canonical correlation analysis techniques

This paper describes various speaker normalization and adaptation techniques of a knowledge data base or reference templates to new speakers in automatic speech recognition (ASR). It focuses on a technique for learning spectral transformations, based on a statistical-analysis tool (canonical correlation analysis), to adapt a standard dictionary to arbitrary speakers. The proposed method should permit to improve speaker independence in large vocabulary ASR. Application to an isolated word recognizer improved a 70% correct score to 87%. A dynamic aspect of the speaker adaptation procedure is introduced and evaluated in a particular strategy.

Relationship of Selected Tests of Leg Strength and Leg Power on College Men

Abstract Thirty-eight male university students served as Ss. They were tested for leg power using seven tests and for leg strength by means of cable tensiometer methods. The power tests were the vertical jump, standing broad jump, chalk board jump, 5-yd. sprint, 10-yd. sprint, running 5-yd. sprint, and a criterion power score consisting of a vertical jump task performed on a force platform. The leg strength tests were hip extension, knee extension, and ankle plantar flexion with scores recorded for both the dominant and nondominant legs. Data were treated by the product-moment, multiple correlation, canonical correlation, and factor analysis techniques. All the computed correlations were low to moderate suggesting that the contribution of strength to power is minor and that power is a more complex entity.