Non-linear Canonical Correlation Analysis using a RBF networks
نویسندگان
چکیده
A non-linear version of the multivariate statistical technique of canonical correlation analysis (CCA) is proposed through the integration of a radial basis function (RBF) network. The advantage of the RBF network is that the solution of linear CCA can be used to train the network and hence the training effort is minimal. Also the canonical variables can be extracted simultaneously. It is shown that the proposed technique can be used to extract non-linear structures inherent within a data set.
منابع مشابه
Estimation of Soil Infiltration in Agricultural and Pasture Lands using Artificial Neural Networks and Multiple Regressions
Common methods to determine the soil infiltration need extensive time and are expensive. However, the existence of non-linear behaviors in soil infiltration makes it difficult to be modeled. With regards to the difficulties of direct measurement of soil infiltration, the use of indirect methods toestimate this parameter has received attention in recent years. Despite the existence of various th...
متن کاملPrediction of Red Mud Bound-Soda Losses in Bayer Process Using Neural Networks
In the Bayer process, the reaction of silica in bauxite with caustic soda causes the loss of great amount of NaOH. In this research, the bound-soda losses in Bayer process solid residue (red mud) are predicted using intelligent techniques. This method, based on the application of regression and artificial neural networks (AAN), has been used to predict red mud bound-soda losses in Iran Alumina C...
متن کاملGeneralization of Canonical Correlation Analysis from Multivariate to Functional Cases and its related problems
In multivariate cases, the aim of canonical correlation analysis (CCA) for two sets of variables x and y is to obtain linear combinations of them so that they have the largest possible correlation. However, when x and y are continouse functions of another variable (generally time) in nature, these two functions belong to function spaces which are of infinite dimension, and CCA for them should b...
متن کاملForecasting and Sensitivity Analysis of Monthly Evaporation from Siah Bisheh Dam Reservoir using Artificial neural Networks combined with Genetic Algorithm
Evaporation process, the main component of the water cycle in nature, is essential in agricultural studies, hydrology and meteorology, the operation of reservoirs, irrigation and drainage systems, irrigation scheduling and management of water resources. Various methods have been presented for estimating evaporation from free surface including water budget method, evaporation from pan and experi...
متن کاملAdaptive Predictive Controllers Using a Growing and Pruning RBF Neural Network
An adaptive version of growing and pruning RBF neural network has been used to predict the system output and implement Linear Model-Based Predictive Controller (LMPC) and Non-linear Model-based Predictive Controller (NMPC) strategies. A radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.An Unscented Kal...
متن کامل