Abstract: The device determines the weighting coefficients to be applied to N digital source signals to form a composite signal. The first- to third-order moments of the composite signal must respectively present mean value, variance and skewness characteristics predefined by a user. The device introduces an additional variable, in the form of a weighting matrix W. The vector w being the vector of the weighting coefficients and wT the transpose of the vector w, the difference W?wwT is a positive semidefinite matrix. Moreover, the device performs linearization, around a vector wref of reference weighting coefficients, of the skewness constraint on the third-order moments using a matrix A = [ W w w T 1 ] as further intermediate variable.

Abstract: The device determines the weighting coefficients to be applied to N digital source signals to form a composite signal. The first- to third-order moments of the composite signal must respectively present mean value, variance and skewness characteristics predefined by a user. The device introduces an additional variable, in the form of a weighting matrix W. The vector w being the vector of the weighting coefficients and wT the transpose of the vector w, the difference W?wwT is a positive semidefinite matrix. Moreover, the device performs linearization, around a vector wref of reference weighting coefficients, of the skewness constraint on the third-order moments using a matrix A = [ W w w T 1 ] as further intermediate variable.

Abstract: The correction device comprises a block for decomposition into total proper elements, according to the Kato spectral decomposition method, of the covariance matrix to be corrected. The block supplies to a correction block the total proper values and the total projectors of the covariance matrix, as well as first coefficient vectors for the combination of the source signals of the covariance matrix. The correlation block estimates the reconstructed variances of combinations of the source signals using the first coefficient vectors and second used-defined coefficient vectors. It looks for the corrected matrix closest to the matrix to be corrected, in relation to the variances and total projectors while is applying a quasi-Newton type method to the dual of a semi-defined lesser error square programme.

Abstract: The correction device comprises a block for decomposition into total proper elements, according to the Kato spectral decomposition method, of the covariance matrix to be corrected. The block supplies to a correction block the total proper values and the total projectors of the covariance matrix, as well as first coefficient vectors for the combination of the source signals of the covariance matrix. The correlation block estimates the reconstructed variances of combinations of the source signals using the first coefficient vectors and second used-defined coefficient vectors. It looks for the corrected matrix closest to the matrix to be corrected, in relation to the variances and total projectors while is applying a quasi-Newton type method to the dual of a semi-defined lesser error square programme.