Nonlinear Canonical Correlation Analysis:A Compressed Representation Approach
نویسندگان
چکیده
منابع مشابه
Nonlinear Canonical Correlation Analysis of the Tropical Pacific Climate Variability Using a Neural Network Approach
Recent advances in neural network modeling have led to the nonlinear generalization of classical multivariate analysis techniques such as principal component analysis and canonical correlation analysis (CCA). The nonlinear canonical correlation analysis (NLCCA) method is used to study the relationship between the tropical Pacific sea level pressure (SLP) and sea surface temperature (SST) fields...
متن کاملRobust nonlinear canonical correlation analysis: application to seasonal climate forecasting
Robust variants of nonlinear canonical correlation analysis (NLCCA) are introduced to improve performance on datasets with low signal-to-noise ratios, for example those encountered when making seasonal climate forecasts. The neural network model architecture of standard NLCCA is kept intact, but the cost functions used to set the model parameters are replaced with more robust variants. The Pear...
متن کاملNonlinear Generalized Canonical Correlation Analysis by Neural Network Models
A method ofK-set canonical correlation analysis capable of joint multivariate nonlinear transformations of data was proposed. The method consists ofK nonlinear data transformation modules, each of which is a multilayered feed-forward network, and one integrator module which combines information from the K transformation modules. The proposed method is useful for integrating information from K c...
متن کاملCanonical representation for approximating solution of fuzzy polynomial equations
In this paper, the concept of canonical representation is proposed to find fuzzy roots of fuzzy polynomial equations. We transform fuzzy polynomial equations to system of crisp polynomial equations, this transformation is perform by using canonical representation based on three parameters Value, Ambiguity and Fuzziness.
متن کاملHuman Face Recognition in wavelet compressed domain using Canonical Correlation Analysis
This paper explores the possibility of implementing face recognition systems directly into wavelet based compressed domain. This is accomplished by stopping the decompression process after entropy decoding and providing the entropy points to face recognition systems as input. A novel approach for efficient face recognition in compressed domain has been implemented using 2-dimensional Canonical ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Entropy
سال: 2020
ISSN: 1099-4300
DOI: 10.3390/e22020208