Abstract: Continuous wavelet transforms of multivariable vector function spaces are discussed. In the weak topology we get the reconstruction formulas of the continuous wavelet transforms of ...

We propose a multivariate regression model to deal with multiple continuous bounded data. The proposed model is based on second-moment assumptions, only. We adopted the quasi-score and Pearson ...

Abstract: This chapter introduces two types of practical multivariable controllers. These controllers are capable of tracking step reference signals and rejecting low frequency disturbances. The ...

The multivariable fractional polynomial (MFP) approach combines variable selection using backward elimination with a function selection procedure (FSP) for fractional polynomial (FP) functions. It is ...

Neural networks are universal function approximators, which means that given enough parameters, a neural net can approximate any multivariable continuous function to any desired level of accuracy. The ...

During the Oxford Conference of the Econometric Society in 1936, Ragnar Frisch proposed a problem of characterization of distributions based on the property of linear regression of one linear function ...