946 resultados para second-order inelastic analysis
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2000 Mathematics Subject Classification: 35J70, 35P15.
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2000 Mathematics Subject Classification: 34C10, 34C15.
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2000 Mathematics Subject Classification: 34C10, 34C15.
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2000 Mathematics Subject Classification: 39A10.
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We propose a novel random DFB fiber laser based Raman amplification using bidirectional second-order pumping. This extends the reach of 116 Gb/s DP-QPSK WDM transmission up to 7915 km, compared with other Raman amplification techniques.
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We demonstrate that a distributed Raman amplification scheme based on random distributed feedback (DFB) fiber laser enables bidirectional second-order Raman pumping without increasing relative intensity noise (RIN) of the signal. This extends the reach of 10 × 116 Gb/s DP-QPSK WDM transmission up to 7915 km, compared with conventional Raman amplification schemes. Moreover, this scheme gives the longest maximum transmission distance among all the Raman amplification schemes presented in this paper, whilst maintaining relatively uniform and symmetric signal power distribution, and is also adjustable in order to be highly compatible with different nonlinearity compensation techniques, including mid-link optical phase conjugation (OPC) and nonlinear Fourier transform (NFT).
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In this Letter, we theoretically and numerically analyze the performance of coherent optical transmission systems that deploy inline or transceiver based nonlinearity compensation techniques. For systems where signal-signal nonlinear interactions are fully compensated, we find that beyond the performance peak the signal-to-noise ratio degradation has a slope of 3 dBSNR/dBPower suggesting a quartic rather than quadratic dependence on signal power. This is directly related to the fact that signals in a given span will interact not only with linear amplified spontaneous emission noise, but also with the nonlinear four-wave mixing products generated from signal-noise interaction in previous (hitherto) uncompensated spans. The performance of optical systems employing different nonlinearity compensation schemes were numerically simulated and compared against analytical predictions, showing a good agreement within a 0.4 dB margin of error.
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We experimentally investigate three Raman fibre laser based amplification techniques with second-order bidirectional pumping. Relatively intensity noise (RIN) being transferred to the signal can be significantly suppressed by reducing first-order reflection near the input end. © 2015 OSA.
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Prices of U.S. Treasury securities vary over time and across maturities. When the market in Treasurys is sufficiently complete and frictionless, these prices may be modeled by a function time and maturity. A cross-section of this function for time held fixed is called the yield curve; the aggregate of these sections is the evolution of the yield curve. This dissertation studies aspects of this evolution. ^ There are two complementary approaches to the study of yield curve evolution here. The first is principal components analysis; the second is wavelet analysis. In both approaches both the time and maturity variables are discretized. In principal components analysis the vectors of yield curve shifts are viewed as observations of a multivariate normal distribution. The resulting covariance matrix is diagonalized; the resulting eigenvalues and eigenvectors (the principal components) are used to draw inferences about the yield curve evolution. ^ In wavelet analysis, the vectors of shifts are resolved into hierarchies of localized fundamental shifts (wavelets) that leave specified global properties invariant (average change and duration change). The hierarchies relate to the degree of localization with movements restricted to a single maturity at the base and general movements at the apex. Second generation wavelet techniques allow better adaptation of the model to economic observables. Statistically, the wavelet approach is inherently nonparametric while the wavelets themselves are better adapted to describing a complete market. ^ Principal components analysis provides information on the dimension of the yield curve process. While there is no clear demarkation between operative factors and noise, the top six principal components pick up 99% of total interest rate variation 95% of the time. An economically justified basis of this process is hard to find; for example a simple linear model will not suffice for the first principal component and the shape of this component is nonstationary. ^ Wavelet analysis works more directly with yield curve observations than principal components analysis. In fact the complete process from bond data to multiresolution is presented, including the dedicated Perl programs and the details of the portfolio metrics and specially adapted wavelet construction. The result is more robust statistics which provide balance to the more fragile principal components analysis. ^
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An examination of the efficacy of religious studies scholarship through a Kuhnian lens.
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Cognitive radio (CR) was developed for utilizing the spectrum bands efficiently. Spectrum sensing and awareness represent main tasks of a CR, providing the possibility of exploiting the unused bands. In this thesis, we investigate the detection and classification of Long Term Evolution (LTE) single carrier-frequency division multiple access (SC-FDMA) signals, which are used in uplink LTE, with applications to cognitive radio. We explore the second-order cyclostationarity of the LTE SC-FDMA signals, and apply results obtained for the cyclic autocorrelation function to signal detection and classification (in other words, to spectrum sensing and awareness). The proposed detection and classification algorithms provide a very good performance under various channel conditions, with a short observation time and at low signal-to-noise ratios, with reduced complexity. The validity of the proposed algorithms is verified using signals generated and acquired by laboratory instrumentation, and the experimental results show a good match with computer simulation results.
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The ability to predict the properties of magnetic materials in a device is essential to ensuring the correct operation and optimization of the design as well as the device behavior over a wide range of input frequencies. Typically, development and simulation of wide-bandwidth models requires detailed, physics-based simulations that utilize significant computational resources. Balancing the trade-offs between model computational overhead and accuracy can be cumbersome, especially when the nonlinear effects of saturation and hysteresis are included in the model. This study focuses on the development of a system for analyzing magnetic devices in cases where model accuracy and computational intensity must be carefully and easily balanced by the engineer. A method for adjusting model complexity and corresponding level of detail while incorporating the nonlinear effects of hysteresis is presented that builds upon recent work in loss analysis and magnetic equivalent circuit (MEC) modeling. The approach utilizes MEC models in conjunction with linearization and model-order reduction techniques to process magnetic devices based on geometry and core type. The validity of steady-state permeability approximations is also discussed.
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"CM-1034."