On approximation of stable linear dynamical systems using Laguerre and Kautz functions
Automatica (Journal of IFAC)
Optimal Laguerre filters for sigma-delta demodulator circuits
Signal Processing
Adaptive Laguerre network realization
Signal Processing - Special section on signal processing technologies for short burst wireless communications
Reduced complexity Volterra models for nonlinear system identification
EURASIP Journal on Applied Signal Processing - Nonlinear signal and image processing - part I
Baseband Volterra filters for implementing carrier basednonlinearities
IEEE Transactions on Signal Processing
Parallel-cascade realizations and approximations of truncatedVolterra systems
IEEE Transactions on Signal Processing
Efficient algorithms for Volterra system identification
IEEE Transactions on Signal Processing
Automatica (Journal of IFAC)
Brief Optimal expansions of discrete-time Volterra models using Laguerre functions
Automatica (Journal of IFAC)
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Volterra models are very useful for signal and system representation due to their general nonlinear structure and their property of linearity with respect to their parameters, the kernel coefficients. However, when using Volterra models we are confronted with a complexity problem that results from the very large number of parameters required by such models. Expanding the kernels on a generalized orthonormal basis allows to significantly reduce this parametric complexity. In the present paper, a new constructive procedure is described for selecting such a generalized orthonormal basis in the case of second-order Volterra systems. A pruning method is also proposed for eliminating the least significant terms in the kernel expansions.