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Identification of Third-Order Volterra-PARAFAC Models Based on PARAFAC Decomposition Using a Tensor Approach
| Content Provider | Semantic Scholar |
|---|---|
| Author | Ahmed, Zouhour Ben Derbel, Nabil |
| Copyright Year | 2017 |
| Abstract | Volterra models are very useful for representing nonlinear systems with vanishing memory. The main drawback of these models is their huge number of parameters to be estimated. In this paper, we present a new class of Volterra models, called Volterra-Parafac models, with a reduced parametric complexity, by considering Volterra kernels of order (p > 2) as symmetric tensors and by using a parallel factor (PARAFAC) decomposition. This paper is concerned with the problem of identification of third-order Volterra-PARAFAC models. Two types of algorithms are proposed for estimating the parameters of these models when input-output signals and kernel coefficients are real valued. The first is called Levenberg-Marquardt algorithm and the second is the Partial Update LMS algorithms. Some simulation results illustrate the proposed identification methods. |
| File Format | PDF HTM / HTML |
| Volume Number | 13 |
| Alternate Webpage(s) | http://www.wseas.org/multimedia/journals/signal/2017/a495814-630.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
