1,721,424 research outputs found
Bayesian decision feedback equaliser for overcoming co-channel interference
No full textThe authors derive a Bayesian decision feedback equaliser which incorporates co-channel interference compensation. By exploiting the structure of co-channel interfering signals, the proposed Bayesian decision feedback equaliser is able to distinguish an interfering signal from white noise and utilises this information to improve performance. Adaptive implementation of this Bayesian decision feedback equaliser includes identifying the channel model using the least mean square algorithm and estimating the co-channel states by means of an unsupervised clustering scheme. Simulation involving a binary signal constellation is used to compare both the theoretical and adaptive performance of this Bayesian decision feedback equaliser with those of the maximum likelihood sequence estimator. The results obtained indicate that, in the presence of severe co-channel interference, the Bayesian decision feedback equaliser employing the proposed simple scheme to compensate co-channel interference can outperform the maximum likelihood sequence estimator that only treats co-channel interference as an additional coloured noise.</p
Fast blind equalisation based on a Bayesian decision feedback equaliser
No full textA blind Bayesian decision feedback equaliser is derived for joint channel and data estimation. The nature or this algorithm leads to an efficient parallel implementation. Convergence can be achieved in less than 50 symbols when a binary symbol constellation is used.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Complex-valued radial basis function networks, Part II: application to digital communications channel equalisation
No full textAdaptive Bayesian decision feedback equaliser based on a radial basis function network
No full textThe authors derive a novel Bayesian decision feedback equalizer (DFE) for digital communications channel equalization. It is shown how decision feedback is utilized to improve equalizer performance as well as to reduce computational complexity. The relationship between the Bayesian solution and the radial basis function (RBF) network is emphasized and two adaptive schemes are described for implementing the Bayesian DFE using the RBF network. The maximum likelihood sequence estimator (MLSE) and the conventional DFE are used as two benchmarks to assess the performance of the Bayesian DFE
Blind channel identification based on higher-order cumulant fitting using genetic algorithms
No full textA family of blind equalisation algorithms identifies a channel model based on a higher-order cumulant (HOC) fitting approach. Since HOC cost functions are multimodal, gradient search techniques require a good initial estimate to avoid converging to local minima. We present a blind identification scheme which uses genetic algorithms (GAS) to optimise a HOC cost function. Because GAS are efficient global optimal search strategies, the proposed method guarantees to find a global optimal channel estimate. A micro- GA implementation is adopted to further enhance computational efficiency. As is demonstrated in computer simulation, this GA based scheme is robust and accurate, and has a fast convergence performance
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