943 resultados para Frequency Domain Spectroscopy (FDS)


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A practical single-carrier (SC) block transmission with frequency domain equalisation (FDE) system can generally be modelled by the Hammerstein system that includes the nonlinear distortion effects of the high power amplifier (HPA) at transmitter. For such Hammerstein channels, the standard SC-FDE scheme no longer works. We propose a novel Bspline neural network based nonlinear SC-FDE scheme for Hammerstein channels. In particular, we model the nonlinear HPA, which represents the complex-valued static nonlinearity of the Hammerstein channel, by two real-valued B-spline neural networks, one for modelling the nonlinear amplitude response of the HPA and the other for the nonlinear phase response of the HPA. We then develop an efficient alternating least squares algorithm for estimating the parameters of the Hammerstein channel, including the channel impulse response coefficients and the parameters of the two B-spline models. Moreover, we also use another real-valued B-spline neural network to model the inversion of the HPA’s nonlinear amplitude response, and the parameters of this inverting B-spline model can be estimated using the standard least squares algorithm based on the pseudo training data obtained as a byproduct of the Hammerstein channel identification. Equalisation of the SC Hammerstein channel can then be accomplished by the usual one-tap linear equalisation in frequency domain as well as the inverse Bspline neural network model obtained in time domain. The effectiveness of our nonlinear SC-FDE scheme for Hammerstein channels is demonstrated in a simulation study.

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The molecular arrangement in organic thin films is crucial for their increasing technological applications. Here, we use vibrational spectroscopy by sum-frequency generation (SFG) to study the ordering of polyelectrolyte layers adsorbed on silica for all steps of layer-by-layer (LbL) self-assembly. In situ measurements during adsorption and rinsing showed that the adsorbed polymer has a disordered conformation and confirmed surface charge overcompensation upon polyelectrolyte adsorption by probing the interfacial electric field. In dry films, the polymer chains acquired a net orientational ordering, which was affected, however, by the adsorption of subsequent layers. Such a detailed characterization may allow the control of LbL film structure and functionality with unprecedented power.

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Sum-Frequency Vibrational Spectroscopy (SFVS) has been used to investigate the effect of nitrogen-flow drying on the molecular ordering of Layer-by-Layer (LbL) films of poly(allylamine hydrochloride) (PAH) alternated with poly(styrene sulfonate) (PSS). We find that films dried by spontaneous water evaporation are more ordered and homogeneous than films dried by nitrogen flow. The latter are quite inhomogeneous and may have regions with highly disordered polymer conformation. We propose that drying by spontaneous water evaporation reduces the effect of drag by the drying front, while during nitrogen-flow drying the fast evaporation of water ""freezes"" the disordered conformation of adsorbed polyelectrolyte molecules. These findings are important for many applications of LbL films, since device performance usually depends on film morphology and its molecular structure.

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Fluorescence quenching of meso-tetrakis-4-sulfonatophenyl (TPPS4) and meso-tetrakis-4-N-methylpyridil (TMPyP) porphyrins is studied in aqueous solution and upon addition of micelles of sodium dodecylsulfate (SDS), cetyltrimethylammonium chloride (CTAC), N-hexadecyl-N,N-dimethyl-3-ammonio-1-propanesulfonate (HPS) and t-octylphenoxypolyethoxyethanol (Triton X-100). Potassium iodide (KI) was used as quencher. Steady-state Stern-Volmer plots were best fitted by a quadratic equation, including dynamic (K-D) and static (K-s) quenching. Ks was significantly smaller than K-D. Frequency-domain fluorescence lifetimes allowed estimating bimolecular quenching constants, k(q). At 25 degrees C, in aqueous solution, TMPyP shows k(q), values a factor of 2-3 higher than the diffusional limit. TPPS4 shows collisional quenching with pH dependent k(q) values. For TMPyP quenching results are consistent with reported binding constants: a significant reduction of quenching takes place for SDS, a moderate reduction is observed for H PS and almost no change is seen for Triton X-100. Similar data were obtained at 50 C. For CTAC-TPPS4 system an enhancement of quenching was observed as compared to pure buffer. This is probably associated to accumulation of iodide at the cationic micellar interface. The attraction between CTAC headgroups and 1(-), and repulsion between SDS and 1(-), enhances and reduces the fluorescence quenching, respectively, of porphyrins located at the micellar interface. The small quenching of TPPS4 in Triton X-100 is consistent with strong binding as reported in the literature. (C) 2008 Elsevier B.V. All rights reserved.

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Fabric pilling is a serious problem for the apparel industry. Resistance to pilling is normally tested by simulated accelerated wear and manual assessment of degree of pilling based on a visual comparison of the sample to a set of test images. A number of automated systems based on image analysis have been developed. The authors propose new methods of image analysis based on the two-dimensional wavelet transform to objectively measure the pilling intensity in sample images. Initial work employed the detail coefficients of the two-dimensional discrete wavelet transform (2DDWT) as a measure of the pilling intensity of woven/knitted fabrics.

This method is shown to be robust to image translation and brightness variation. Using the approximation coefficients of the 2DDWT, the method is extended to non-woven pilling image sets. Wavelet texture analysis (WTA) combined with principal components analysis are shown to produce a richer texture description of pilling for analysis and classification. Finally, employing the two-dimensional dual-tree complex wavelet transform as the basis for the WTA feature vector is shown to produce good automated classification on a range of standard pilling image sets.

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This paper presents a new time-frequency approach to the underdetermined blind source separation using the parallel factor decomposition of third-order tensors. Without any constraint on the number of active sources at an auto-term time-frequency point, this approach can directly separate the sources as long as the uniqueness condition of parallel factor decomposition is satisfied. Compared with the existing two-stage methods where the mixing matrix should be estimated at first and then used to recover the sources, our approach yields better source separation performance in the presence of noise. Moreover, the mixing matrix can be estimated at the same time of the source separation process. Numerical simulations are presented to show the superior performance of the proposed approach to some of the existing two-stage blind source separation methods that use the time-frequency representation as well.

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A multiple-iteration constrained conjugate gradient (MICCG) algorithm and a single-iteration constrained conjugate gradient (SICCG) algorithm are proposed to realize the widely used frequency-domain minimum-variance-distortionless-response (MVDR) beamformers and the resulting algorithms are applied to speech enhancement. The algorithms are derived based on the Lagrange method and the conjugate gradient techniques. The implementations of the algorithms avoid any form of explicit or implicit autocorrelation matrix inversion. Theoretical analysis establishes formal convergence of the algorithms. Specifically, the MICCG algorithm is developed based on a block adaptation approach and it generates a finite sequence of estimates that converge to the MVDR solution. For limited data records, the estimates of the MICCG algorithm are better than the conventional estimators and equivalent to the auxiliary vector algorithms. The SICCG algorithm is developed based on a continuous adaptation approach with a sample-by-sample updating procedure and the estimates asymptotically converge to the MVDR solution. An illustrative example using synthetic data from a uniform linear array is studied and an evaluation on real data recorded by an acoustic vector sensor array is demonstrated. Performance of the MICCG algorithm and the SICCG algorithm are compared with the state-of-the-art approaches.

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The Patellofemoral Pain Syndrome (PFPS), has a multifactorial etiology and affects approximately 7 to 15% of the population, mostly women, youth, adults and active persons. PFPS causes anterior or retropatelar pain that is exacerbated during functional motor gestures, such as up and down stairs or spending long periods of time sitting, squatting or kneeling. As the diagnostic evaluation of this syndrome is still indirect, different mechanisms and methodologies try to make a classification that distinguishes patients with PFPS in relation to asymptomatic. Thereby, the purpose of this investigation was to determine the characteristics of the electromyographic (EMG) signal in the frequency domain of the vastus medialis oblique (VMO) and vastus lateralis (VL) in patients with PFPS, during the ascent of stairs. 33 young women (22 control group and 11 PFPS group), were evaluated by EMG during ascent of stairs. The VMO mean power frequency (MPF) and the VL frequency 95% (F95) were lower in symptomatic individuals. This may be related to the difference in muscle recruitment strategy exerted by each muscle in the PFPS group compared to the control group.

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In the optimization or parametric analyses of risers, several configurations must be analyzed. It is laborious to perform time domain solutions for the dynamic analysis, since they are time-consuming tasks. So, frequency domain solutions appear to be a possible alternative, mainly in the early stages of a riser design. However, frequency domain analysis is linear and requires that nonlinear effects are treated. The aim of this paper is to present a possible way to treat some of these nonlinearities, using an iterative process together with an analytical correction, and compare the results of a frequency domain analysis with the those of a full nonlinear analysis. [DOI: 10.1115/1.4006149]

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Among the experimental methods commonly used to define the behaviour of a full scale system, dynamic tests are the most complete and efficient procedures. A dynamic test is an experimental process, which would define a set of characteristic parameters of the dynamic behaviour of the system, such as natural frequencies of the structure, mode shapes and the corresponding modal damping values associated. An assessment of these modal characteristics can be used both to verify the theoretical assumptions of the project, to monitor the performance of the structural system during its operational use. The thesis is structured in the following chapters: The first introductive chapter recalls some basic notions of dynamics of structure, focusing the discussion on the problem of systems with multiply degrees of freedom (MDOF), which can represent a generic real system under study, when it is excited with harmonic force or in free vibration. The second chapter is entirely centred on to the problem of dynamic identification process of a structure, if it is subjected to an experimental test in forced vibrations. It first describes the construction of FRF through classical FFT of the recorded signal. A different method, also in the frequency domain, is subsequently introduced; it allows accurately to compute the FRF using the geometric characteristics of the ellipse that represents the direct input-output comparison. The two methods are compared and then the attention is focused on some advantages of the proposed methodology. The third chapter focuses on the study of real structures when they are subjected to experimental test, where the force is not known, like in an ambient or impact test. In this analysis we decided to use the CWT, which allows a simultaneous investigation in the time and frequency domain of a generic signal x(t). The CWT is first introduced to process free oscillations, with excellent results both in terms of frequencies, dampings and vibration modes. The application in the case of ambient vibrations defines accurate modal parameters of the system, although on the damping some important observations should be made. The fourth chapter is still on the problem of post processing data acquired after a vibration test, but this time through the application of discrete wavelet transform (DWT). In the first part the results obtained by the DWT are compared with those obtained by the application of CWT. Particular attention is given to the use of DWT as a tool for filtering the recorded signal, in fact in case of ambient vibrations the signals are often affected by the presence of a significant level of noise. The fifth chapter focuses on another important aspect of the identification process: the model updating. In this chapter, starting from the modal parameters obtained from some environmental vibration tests, performed by the University of Porto in 2008 and the University of Sheffild on the Humber Bridge in England, a FE model of the bridge is defined, in order to define what type of model is able to capture more accurately the real dynamic behaviour of the bridge. The sixth chapter outlines the necessary conclusions of the presented research. They concern the application of a method in the frequency domain in order to evaluate the modal parameters of a structure and its advantages, the advantages in applying a procedure based on the use of wavelet transforms in the process of identification in tests with unknown input and finally the problem of 3D modeling of systems with many degrees of freedom and with different types of uncertainty.

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Coronary late stent thrombosis, a rare but devastating complication, remains an important concern in particular with the increasing use of drug-eluting stents. Notably, pathological studies have indicated that the proportion of uncovered coronary stent struts represents the best morphometric predictor of late stent thrombosis. Intracoronary optical frequency domain imaging (OFDI), a novel second-generation optical coherence tomography (OCT)-derived imaging method, may allow rapid imaging for the detection of coronary stent strut coverage with a markedly higher precision when compared with intravascular ultrasound, due to a microscopic resolution (axial approximately 10-20 microm), and at a substantially increased speed of image acquisition when compared with first-generation time-domain OCT. However, a histological validation of coronary OFDI for the evaluation of stent strut coverage in vivo is urgently needed. Hence, the present study was designed to evaluate the capacity of coronary OFDI by electron (SEM) and light microscopy (LM) analysis to detect and evaluate stent strut coverage in a porcine model.

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Alternans of cardiac action potential duration (APD) is a well-known arrhythmogenic mechanism which results from dynamical instabilities. The propensity to alternans is classically investigated by examining APD restitution and by deriving APD restitution slopes as predictive markers. However, experiments have shown that such markers are not always accurate for the prediction of alternans. Using a mathematical ventricular cell model known to exhibit unstable dynamics of both membrane potential and Ca2+ cycling, we demonstrate that an accurate marker can be obtained by pacing at cycle lengths (CLs) varying randomly around a basic CL (BCL) and by evaluating the transfer function between the time series of CLs and APDs using an autoregressive-moving-average (ARMA) model. The first pole of this transfer function corresponds to the eigenvalue (λalt) of the dominant eigenmode of the cardiac system, which predicts that alternans occurs when λalt≤−1. For different BCLs, control values of λalt were obtained using eigenmode analysis and compared to the first pole of the transfer function estimated using ARMA model fitting in simulations of random pacing protocols. In all versions of the cell model, this pole provided an accurate estimation of λalt. Furthermore, during slow ramp decreases of BCL or simulated drug application, this approach predicted the onset of alternans by extrapolating the time course of the estimated λalt. In conclusion, stochastic pacing and ARMA model identification represents a novel approach to predict alternans without making any assumptions about its ionic mechanisms. It should therefore be applicable experimentally for any type of myocardial cell.

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To demonstrate the feasibility and potential usefulness of an offline fusion of matched optical coherence tomography (OCT) and intravascular ultrasound (IVUS)/virtual histology (IVUS-VH) images.