1,721,096 research outputs found
Filter for the equalization and/or linearization of non-Linear systems
No full textThe present invention refers to a reverse filter of the pth order, p being a positive integer number, of a non linear system modelled by means of a Volterra filter, implemented by means of the cascade of the reverse filter of the linear part of the model and of p-1 cascaded cells; the main characteristic consists in the fact that each one of said cells comprises a first branch where there is present the output signal of the reverse filter of the linear part, and a second branch constituted by the cascade of the non linear part of the model and the reverse filter of the linear part of the model. Eliminating the reverse filter in cascade with the p-1 cells pre-linearizing and post- linearizing filters are obtained
The road of an acoustic echo Controller for mobile telephony from product definition till production
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Nonlinear system identification using quasi-perfect periodic sequences
No full textThe paper discusses a novel sub-class of linear-in-the-parameters nonlinear filters, the Legendre nonlinear filters. The novel sub-class combines the best characteristics of truncated Volterra filters and of the recently introduced even mirror Fourier nonlinear filters, in particular: (i) Legendre nonlinear filters can arbitrarily well approximate any causal, time-invariant, finite-memory, continuous, nonlinear system; (ii) their basis functions are polynomials, specifically, products of Legendre polynomial expansions of the input signal samples; (iii) the basis functions are also mutually orthogonal for white uniform input signals and thus, in adaptive applications, gradient descent algorithms with fast convergence speed can be devised; (iv) perfect periodic sequences can be developed for the identification of Legendre nonlinear filters. A periodic sequence is perfect for a certain nonlinear filter if all cross-correlations between two different basis functions, estimated over a period, are zero. Using perfect periodic sequences as input signals permits the identification of the most relevant basis functions of an unknown nonlinear system by means of the cross-correlation method. Experimental results involving identification of real nonlinear systems illustrate the effectiveness and efficiency of this approach and the potentialities of Legendre nonlinear filters
Efficient NLMS and RLS algorithms for perfect and imperfect periodic sequences
No full textThe paper discusses computationally efficient NLMS and RLS algorithms for perfect and imperfect periodic excitation sequences. The most interesting aspect of these algorithms is that they are exact LMS and RLS algorithms suitable for identification and tracking of every linear system and they require a real-time computational effort of just a multiplication, an addition and a subtraction per sample time. Moreover, the algorithms have convergence and tracking properties that can be better than or comparable with the NLMS algorithm for white noise input. The transient and steady state behavior of the algorithms and their tracking properties are also studied in the paper
A study about Chebyshev nonlinear filters
Full text linkThe paper studies a novel family of nonlinear filters based on Chebyshev polynomials of the first kind, the Chebyshev nonlinear filters. This family shares many of the characteristics of the recently introduced Legendre and even mirror Fourier nonlinear filters, but has also peculiar properties. Chebyshev nonlinear filters belong to the class of linear-in-the-parameters nonlinear filters. Their basis functions are polynomials, specifically, products of Chebyshev polynomial expansions of the input signal samples. According to the Stone–Weierstrass theorem, they are universal approximators for causal, time-invariant, finite-memory, continuous, nonlinear systems. Their basis functions are mutually orthogonal for white input signals with a particular nonuniform distribution. They admit perfect periodic sequences, i.e., periodic input sequences that guarantee the mutual orthogonality of the basis functions on a finite period. Using perfect periodic input signals, an unknown nonlinear system and its most relevant basis functions can be identified with the cross-correlation method. It is shown in the paper that the perfect periodic sequences of Chebyshev nonlinear filters are simply related to those of even mirror Fourier nonlinear systems. Experimental results involving a real nonlinear system illustrate the potentialities of these filters
Robust Room Impulse Response Measurement Using Perfect Sequences for Legendre Nonlinear Filters
No full textThe paper proposes a novel approach for measuring the room impulse response that is robust toward the nonlinearities affecting the power amplifier or the loudspeaker. The approach is implemented by modeling the acoustic path as a Legendre nonlinear filter and by measuring the first-order kernel using perfect periodic sequences and the cross-correlation method. Perfect sequences for Legendre filters are periodic sequences that guarantee the orthogonality of the Legendre basis functions over a period. They ensure the robustness of the first kernel measurement toward nonlinear distortions. The paper also explains how perfect periodic sequences for Legendre filters that are suitable for room impulse response identification can be developed. Experimental results involving both simulated and real environments illustrate the effectiveness and the robustness of the proposed approach
A Polynomial Multiple Variance Method for Volterra Filter Identification
No full textThe article presents a methodology for accurately estimating the Volterra kernels of a discrete-time nonlinear system, even when the system order exceeds that of the Volterra series model. The approach involves conducting multiple measurements with the same excitation signal, scaled by different gain factors, and deriving the Volterra kernels via interpolation of the measured data. The methodology is thoroughly discussed, and the mean square deviation (MSD) of the estimated coefficients is calculated to determine the optimal gain factors that minimize the MSD. It is demonstrated that the optimal gains are constrained to a specific set of values, which are provided in the article. Experimental results, using both synthetic and real systems, showcase the effectiveness of the proposed methodology
Non-invasive analysis by ultraviolet radiation of ancient manuscripts on parchment support for the detection of faded or no longer visible writings
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