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General Volterra and Swept-Sine Diagonal System Estimation and Modeling Performance

Volterra system modeling performance results are given for various scenarios using both fully-determined and under-determined models. Three nonlinear system estimation methods are presented and compared including a novel and efficient Farina-type Hammerstein algorithm. The diagonal-only Hammerstein methods will not model off-diagonal nonlinear energy for general uncorrelated inputs but will model correlated inputs to some degree. The data matrix estimation methods work for generic input signal types. The nonlinear system must be fully determined to yield best results, but the diagonal-only models are more practical for applications having significantly long memory channels.

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