7 resultados para fourth-order coherence

em CentAUR: Central Archive University of Reading - UK


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This paper introduces a new blind equalisation algorithm for the pulse amplitude modulation (PAM) data transmitted through nonminimum phase (NMP) channels. The algorithm itself is based on a noncausal AR model of communication channels and the second- and fourth-order cumulants of the received data series, where only the diagonal slices of cumulants are used. The AR parameters are adjusted at each sample by using a successive over-relaxation (SOR) scheme, a variety of the ordinary LMS scheme, but with a faster convergence rate and a greater robustness to the selection of the ‘step-size’ in iterations. Computer simulations are implemented for both linear time-invariant (LTI) and linear time-variant (LTV) NMP channels, and the results show that the algorithm proposed in this paper has a fast convergence rate and a potential capability to track the LTV NMP channels.

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An efficient method is described for the approximate calculation of the intensity of multiply scattered lidar returns. It divides the outgoing photons into three populations, representing those that have experienced zero, one, and more than one forward-scattering event. Each population is parameterized at each range gate by its total energy, its spatial variance, the variance of photon direction, and the covariance, of photon direction and position. The result is that for an N-point profile the calculation is O(N-2) efficient and implicitly includes up to N-order scattering, making it ideal for use in iterative retrieval algorithms for which speed is crucial. In contrast, models that explicitly consider each scattering order separately are at best O(N-m/m!) efficient for m-order scattering and often cannot be performed to more than the third or fourth order in retrieval algorithms. For typical cloud profiles and a wide range of lidar fields of view, the new algorithm is as accurate as an explicit calculation truncated at the fifth or sixth order but faster by several orders of magnitude. (C) 2006 Optical Society of America.

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We provide a system identification framework for the analysis of THz-transient data. The subspace identification algorithm for both deterministic and stochastic systems is used to model the time-domain responses of structures under broadband excitation. Structures with additional time delays can be modelled within the state-space framework using additional state variables. We compare the numerical stability of the commonly used least-squares ARX models to that of the subspace N4SID algorithm by using examples of fourth-order and eighth-order systems under pulse and chirp excitation conditions. These models correspond to structures having two and four modes simultaneously propagating respectively. We show that chirp excitation combined with the subspace identification algorithm can provide a better identification of the underlying mode dynamics than the ARX model does as the complexity of the system increases. The use of an identified state-space model for mode demixing, upon transformation to a decoupled realization form is illustrated. Applications of state-space models and the N4SID algorithm to THz transient spectroscopy as well as to optical systems are highlighted.

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This article describes a number of velocity-based moving mesh numerical methods formultidimensional nonlinear time-dependent partial differential equations (PDEs). It consists of a short historical review followed by a detailed description of a recently developed multidimensional moving mesh finite element method based on conservation. Finite element algorithms are derived for both mass-conserving and non mass-conserving problems, and results shown for a number of multidimensional nonlinear test problems, including the second order porous medium equation and the fourth order thin film equation as well as a two-phase problem. Further applications and extensions are referenced.

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This paper uses techniques from control theory in the analysis of trained recurrent neural networks. Differential geometry is used as a framework, which allows the concept of relative order to be applied to neural networks. Any system possessing finite relative order has a left-inverse. Any recurrent network with finite relative order also has an inverse, which is shown to be a recurrent network.

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In recent years, the importance of the corporate brand (e.g. P&G, Nestlé, Unilever) has grown significantly and companies increasingly strive to strengthen their corporate brand. One way to strengthen the corporate brand is portfolio advertisement, in which the corporate brand is presented alongside with several product brands of its portfolio (e.g. VW with its product brands Touareg, Touran, Golf and Polo). The aim of portfolio advertising is to generate a positive image spill-over effect from the product brands onto the corporate brand in order to enhance the consumers’ perceived competence of the corporate brand. In four experimental settings Christian Boris Brunner demonstrates the great potential of portfolio advertising and highlights the risks associated with portfolio advertising in practice. In a first experiment, he compares portfolio advertising with single brand advertisements. Moreover, in case of portfolio advertising he manipulates the fit between the product brands, because the consumer has to establish a logical coherence between the individual brands. However, asconsumers have limited capacity for processing information, special attention should be paid to the number of product brands and to the processing depth of the consumer during confrontation with portfolio advertising. These key factors are taken into consideration in a second extensive experiment involving fictitious corporate and product brands. The effects of portfolio advertising on a product brand are also examined. Furthermore, the strength of product brands, i.e. brand knowledge as well as brand image and consumer’s knowledge of the brands, must be taken into consideration. In a third experiment, both the brand strength of real product brands as well as the fit between product brands are manipulated. Portfolio advertising could also have a positive image spill-over effect when companies introduce a new product brand under the umbrella of the corporate brand while communicating all product brands together. Based on considerations, in a fourth experiment, Christian Boris Brunner shows that portfolio advertising could also have a positive image spill-over effect on a new (unknown) product brand. Concluding his work, Christian Boris Brunner provides implications for future research concerning portfolio advertising as well as the management of a corporate brand in complex brand architectures. Concerning practical implications, these four experiments underline a high relevance to marketing and brand managers, who could increase corporate and product brands’ potential by means of portfolio advertising.

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This paper analyzes the dynamic interactions between real estate markets, in the US and the UK and their macroeconomic environments. We apply a new approach based on a dynamic coherence function (DCF) to study these interactions bringing together different real estate markets (the securitized market, the commercial market and the residential market). The results suggest that there is a common trend that drives the different real estate markets in the UK and the US, particularly in the long run, since they have a similar shape of the DCF. We also find that, in the US, wealth and housing expenditure channels are very conductive during real estate crises. However, in the UK, only the wealth effect is significant as a transmission channel during real estate market downturns. In addition, real estate markets in the UK and the US react differently to institutional shocks. This brings some insights on the conduct of monetary policy in order to avoid disturbances in real estate markets.