1. A method for linearizing a power amplifier having a memory effect with a system for linearizing a power amplifier through digital predistortion, comprising: inputting an input signal sample, predistorting the input signal sample to generate a first and a second intermediate predistorted signal samples, combining the first and the second intermediate predistorted signal samples to obtain an output signal, wherein the inputting, predistorting and combining are performed on an amplifier containing processing circuitry configured to: obtain the input signal sample that depends on an input signal to the power amplifier; predisort the input signal sample using a static weight function to generate the first intermediate predistorted signal sample; predistort the same input signal sample using a dynamic weight function to generate the second intermediate predistorted signal sample; combine additively the first intermediate predistorted signal sample and the second intermediate predistorted signal sample together to obtain an output signal sample of the predistorter, wherein the processing circuitry is further configured to determine the output signal sample of the predistorter using: y WMP ⁡ ( n ) = ∑ i = 0 N s ⁢ ⁢ α i ⁢ w s ⁡ (  x ⁡ ( n )  , i ) ⁢ x ⁡ ( n ) ⁢  x ⁡ ( n )  i + ∑ i = 0 N D ⁢ ⁢ ∑ j = 1 M ⁢ ⁢ β ij ⁢ w D ⁡ (  x ⁡ ( n )  , i , j ) ⁢ x ⁡ ( n - j ) ⁢  x ⁡ ( n - j )  i wherein y WMP (n) and x(n) are output and input baseband complex samples, respectively, α i and β ij are coefficients of the static and dynamic functions of the weighted memory polynomial predistorter, respectively, M is the memory depth of the model, N S and N D are nonlinearity order of the static and dynamic parts of the predistorter, respectively, and w S (|x(n)|,i) and w D (|x(n)|,i,j) are the weight functions applied on the static and dynamic terms of the predistorter, respectively.