7,377 research outputs found
Bounding the Polynomial Approximation Errors of Frequency Response Functions
Frequency response function (FRF) measurements take a central place in the instrumentation and measurement field because many measurement problems boil down to the character- ization of a linear dynamic behavior. The major problems to be faced are leakage and noise errors. The local polynomial method (LPM) was recently presented as a superior method to reduce the leakage errors with several orders of magnitude while the noise sensitivity remained the same as that of the classical windowing methods. The kernel idea of the LPM is a local polynomial approx- imation of the FRF and the leakage errors in a small-frequency band around the frequency where the FRF is estimated. Polyno- mial approximation of FRFs is also present in other measurement and design problems. For that reason, it is important to have a good understanding of the factors that influence the polynomial approximation errors. This article presents a full analysis of this problem and delivers a rule of thumb that can be easily applied in practice to deliver an upper bound on the approximation error of FRFs. It is shown that the approximation error for lowly damped systems is bounded by (B_{LPM}/B_{3dB})^{R+2} with B_{LPM} the local bandwidth of the LPM, R the degree of the local polynomial that is selected to be even (user choices), and B_{3dB} the 3 dB bandwidth of the resonance, which is a system property
Isogeometric FEM-BEM coupled structural-acoustic analysis of shells using subdivision surfaces
We introduce a coupled finite and boundary element formulation for acoustic
scattering analysis over thin shell structures. A triangular Loop subdivision
surface discretisation is used for both geometry and analysis fields. The
Kirchhoff-Love shell equation is discretised with the finite element method and
the Helmholtz equation for the acoustic field with the boundary element method.
The use of the boundary element formulation allows the elegant handling of
infinite domains and precludes the need for volumetric meshing. In the present
work the subdivision control meshes for the shell displacements and the
acoustic pressures have the same resolution. The corresponding smooth
subdivision basis functions have the continuity property required for the
Kirchhoff-Love formulation and are highly efficient for the acoustic field
computations. We validate the proposed isogeometric formulation through a
closed-form solution of acoustic scattering over a thin shell sphere.
Furthermore, we demonstrate the ability of the proposed approach to handle
complex geometries with arbitrary topology that provides an integrated
isogeometric design and analysis workflow for coupled structural-acoustic
analysis of shells
The Error-Pattern-Correcting Turbo Equalizer
The error-pattern correcting code (EPCC) is incorporated in the design of a
turbo equalizer (TE) with aim to correct dominant error events of the
inter-symbol interference (ISI) channel at the output of its matching Viterbi
detector. By targeting the low Hamming-weight interleaved errors of the outer
convolutional code, which are responsible for low Euclidean-weight errors in
the Viterbi trellis, the turbo equalizer with an error-pattern correcting code
(TE-EPCC) exhibits a much lower bit-error rate (BER) floor compared to the
conventional non-precoded TE, especially for high rate applications. A
maximum-likelihood upper bound is developed on the BER floor of the TE-EPCC for
a generalized two-tap ISI channel, in order to study TE-EPCC's signal-to-noise
ratio (SNR) gain for various channel conditions and design parameters. In
addition, the SNR gain of the TE-EPCC relative to an existing precoded TE is
compared to demonstrate the present TE's superiority for short interleaver
lengths and high coding rates.Comment: This work has been submitted to the special issue of the IEEE
Transactions on Information Theory titled: "Facets of Coding Theory: from
Algorithms to Networks". This work was supported in part by the NSF
Theoretical Foundation Grant 0728676
Polynomial-based surrogate modeling of RF and microwave circuits in frequency domain exploiting the multinomial theorem
A general formulation to develop EM-based polynomial surrogate models in frequency domain utilizing the multinomial theorem is presented in this paper. Our approach is especially suitable when the number of learning samples is very limited and no physics-based coarse model is available. We compare our methodology against other four surrogate modeling techniques: response surface modeling, support vector machines, generalized regression neural networks, and Kriging. Results confirm that our modeling approach has the best performance among these techniques when using a very small amount of learning base points on relatively small modeling regions. We illustrate our technique by developing a surrogate model for an SIW interconnect with transitions to microstrip lines, a dual band T-slot PIFA handset antenna, and a high-speed package interconnect. Examples are simulated on a commercially available 3D FEM simulator
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