The assignment of Linear or none-linear SVRM

The model of the Support vector regression machine (SVRM) is based on the elements, which is also presented for the band pass filter. The data is separated into the testing test as well as the training, which is significant for the data mining evaluation. Now the mathematical expression of the Support regression vector machine is express in the below discussion.  

The training dataset   that is the size of the training data. The continuous mapping function f (is attempted by the SVRM form an independent p-dimensional in the input variable vector ( that is output of the dependent by the variable of y , in the linearly combinations of the non-linear transformations results of the input samples. 

To obtain the accurate as well as fast design of the given model, the SVRM model for the basic element is employed. A box of the model for every element is created, including the geometrical dimension of the elements of the input parameters as well as the S parameters of the output elements. The output parameters of the model element are same  that is the magnitude and phase of the parameters. The SVRM model has the output for the parallel operation is run to compose an elements model. Then every element contains the four machines that have the same input due to the four parameters. The Radial Kernel function is exploited on the behalf of SVRM   regression that is explained by, 

Now the above plot is between the frequency and the magnitude   and the angle, it plotted in the MATALB

Y  is a variance for the Kernel function as well as selected in the training phase? The dataset of training for the base elements is obtained through the CST. (Ilarslan & et.al, 2014)The standard non-linear kernel function for the SVRM is the input vectors for the projected into the high dimensional features space, through the sets of basis function. The kernel function is utilizing the inner products among the projections for the input vectors in the feature space.  

The data that is given in the excel file , the SVRM could find the internal connecting links for the input as well as output by the training as well as learning to get the solution of the problem. (Zhang & et.al, 2008)