Nonlinear equalization of Hammerstein OFDM systems

A practical orthogonal frequency-division multiplexing (OFDM) system can generally be modelled by the Hammerstein system that includes the nonlinear distortion effects of the high power amplifier (HPA) at transmitter. In this contribution, we advocate a novel nonlinear equalization scheme for OFDM Hammerstein systems. We model the nonlinear HPA, which represents the static nonlinearity of the OFDM Hammerstein channel, by a B-spline neural network, and we develop a highly effective alternating least squares algorithm for estimating the parameters of the OFDM Hammerstein channel, including channel impulse response coefficients and the parameters of the B-spline model. Moreover, we also use another B-spline neural network to model the inversion of the HPA’s nonlinearity, and the parameters of this inverting B-spline model can easily be estimated using the standard least squares algorithm based on the pseudo training data obtained as a byproduct of the Hammerstein channel identification. Equalization of the OFDM Hammerstein channel can then be accomplished by the usual one-tap linear equalization as well as the inverse B-spline neural network model obtained. The effectiveness of our nonlinear equalization scheme for OFDM Hammerstein channels is demonstrated by simulation results.

B-spline neural network based single-carrier frequency domain equalisation for Hammerstein channels

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.

Adaptive B-spline neural network based nonlinear equalization for high-order QAM systems with nonlinear transmit high power amplifier

High bandwidth-efficiency quadrature amplitude modulation (QAM) signaling widely adopted in high-rate communication systems suffers from a drawback of high peak-toaverage power ratio, which may cause the nonlinear saturation of the high power amplifier (HPA) at transmitter. Thus, practical high-throughput QAM communication systems exhibit nonlinear and dispersive channel characteristics that must be modeled as a Hammerstein channel. Standard linear equalization becomes inadequate for such Hammerstein communication systems. In this paper, we advocate an adaptive B-Spline neural network based nonlinear equalizer. Specifically, during the training phase, an efficient alternating least squares (LS) scheme is employed to estimate the parameters of the Hammerstein channel, including both the channel impulse response (CIR) coefficients and the parameters of the B-spline neural network that models the HPA’s nonlinearity. In addition, another B-spline neural network is used to model the inversion of the nonlinear HPA, and the parameters of this inverting B-spline model can easily be estimated using the standard LS algorithm based on the pseudo training data obtained as a natural byproduct of the Hammerstein channel identification. Nonlinear equalisation of the Hammerstein channel is then accomplished by the linear equalization based on the estimated CIR as well as the inverse B-spline neural network model. Furthermore, during the data communication phase, the decision-directed LS channel estimation is adopted to track the time-varying CIR. Extensive simulation results demonstrate the effectiveness of our proposed B-Spline neural network based nonlinear equalization scheme.

Importance of allelopathy as peudo-mixotrophy for the dynamics and diversity of phytoplankton

Understanding the dynamics and diversity of marine phytoplankton is essential for predicting oceanic primary production, oxygen generation and carbon sequestration. Several top-down and bottom-up factors lead to complex phytoplankton dynamics. Complexities further arise from inter-species interactions within phytoplankton communities. Consequently, some of the basic questions on phytoplankton diversity, identified long ago, still puzzle the ecologists: for example, what regulates the diversity in simple systems where species compete for limiting resources? In this context, allelopathic interaction among phytoplankton species has been identified as a potential driver of their dynamics and regulator of their diversity. This chapter deals with the importance of allelopathy in regulating the outcome of nutrient competition among phytoplankton species, through analysis of a resource-competition model. It demonstrates that, through the mechanism of pseudo-mixotrophy - proposed earlier by the author - allelopathy provides essential growth advantage to weaker competitors, and stabilizes resource competition, which ensures the coexistence of two phytoplankton on a single nutrient. In simple nutrient-phytoplankton interactions where higher-trophic influences are negligible, this mechanism theoretically promotes phytoplankton diversity, and can potentially support high diversity in natural phytoplankton communities.

Thermoelectric properties of TiS2 mechanically alloyed compounds

Bulk polycrystalline samples in the series Ti1−xNbxS2 (0 ≤ x ≤ 0.075) were prepared using mechanical alloying synthesis and spark plasma sintering. X-ray diffraction analysis coupled with high resolution transmission electron microscopy indicates the formation of trigonal TiS2 by high energy ball-milling. The as-synthesized particles consist of pseudo-ordered TiS2 domains of around 20–50 nm, joined by bent atomic planes. This bottom-up approach leads, after spark plasma sintering, to homogeneous solid solutions, with a niobium solubility limit of x = 0.075. Microstructural observations evidence the formation of small crystallites in the bulk compounds with a high density of stacking faults. The large grain boundary concentration coupled with the presence of planar defects, leads to a substantial decrease in the thermal conductivity to 1.8 W/mK at 700 K. This enables the figure of merit to reach ZT = 0.3 at 700 K for x = 0.05, despite the lower electron mobility in mechanically alloyed samples due to small crystallite/grain size and structural defects.

Perception of eating practices and stages of change among Brazilian adolescents

Objective. To evaluate the perception of eating practices and the stages of change among adolescents. Methods. Cross-sectional study involving a representative sample of 390 adolescents from 11 public schools in the city of Piracicaba, Brazil, in 2004. Food consumption was identified by a food frequency questionnaire and the perception of eating practices evaluation was conducted by comparing food consumption and individual classification of healthy aspects of the diet. The participants were classified within stages of change by means of a specific algorithm. A reclassification within new stages of change was proposed to identify adolescents with similar characteristics regarding food consumption and perception. Results. Low consumption of fruit and vegetables and high consumption of sweets and fats were identified. More than 44% of the adolescents had a mistaken perception of their diet. A significant relationship between the stages of change and food consumption was observed. The reclassification among stages of change, through including the pseudo-maintenance and non-reflective action stages was necessary, considering the high proportion of adolescents who erroneously classified their diets as healthy. Conclusion. Classification of the adolescents into stages of change, together with consumption and perception data, enabled identification of groups at risk, in accordance with their inadequate dietary habits and non-recognition of such habits. (C) 2009 Elsevier Inc. All rights reserved.

The RAINY3D Code: The Treatment of Condensation in Nova Remnants during Nebular Phase

Classical nova remnants are important scenarios for improving the photoionization modeling. This work describes the pseudo-three-dimensional code RAINY3D, which drives the photoionization code Cloudy as a subroutine. Photoionization simulations of old nova remnants are also presented and discussed. In these simulations we analyze the effect of condensation in the remnant spectra. The condensed mass fraction affects the Balmer lines by a factor of greater than 4 when compared with homogeneous models, and this directly impacts the shell mass determination. The He II 4686/H beta ratio decreases by a factor of 10 in clumpy shells. These lines are also affected by the clump size and density distributions. The behavior of the strongest nebular line observed in nova remnants is also analyzed for heterogeneous shells. The gas diagnoses in novae ejecta are thought to be more accurate during the nebular phase, but we have determined that at this phase the matter distribution can strongly affect the derived shell physical properties and chemical abundances.

BIRD FORAGING IN ANACARDIUM PATCHES IN CENTRAL BRAZILIAN FIRE BREAKS: RELATIONSHIP BETWEEN FLOCK SIZE AND PATCH SIZE

Fire management ran increase the biomass of some plant species at fire breaks in reserves of the Cerrado. For example, numerous and large patches of monkey-nuts (Anacardium humile, Anacardiaceae) provide abundant food resources for wildlife in the lower strata of savanna woodlands managed by fire. The objective of this study was to examine the exploitation of A. humile patches by birds in managed savanna woodlands (fire breaks) at Emas National Park, southwest Brazil. The relationship between flock size and the size of Anacardium patches were also investigated. Fire breaks were sampled in September and October 2006, when fruits and flowers were abundant. Ara ararauna was often recorded exploiting resources of Anacardium patches. This species and other psittacids (Amazona aestiva, Alipiopsittaca xanthops, and Diopsittaca nobilis) consumed seeds usually on the ground around fruiting patches. Members of Aratinga aurea flocks and Ramphastos toco consumed pseudo-fruits. Larger flocks detected were those of A. aurea and A. ararauna. Groups of A. ararauna that exploited larger patches tended to be larger than flocks that exploited smaller patches. This study suggests that intra- and interspecific interactions and characteristics of Anacardium patches and of the surrounding vegetation are involved in the feeding ecology of birds in the lower stratum of managed woodlands. Fruiting Anacardium patches attract numerous frugivorous birds to fire breaks at Emas National Park. Further research is needed to a better understanding of the influence of fire management on birds in the Cerrado. Accepted 31 July 2009.

Evolutionary fuzzy clustering of relational data

This paper is concerned with the computational efficiency of fuzzy clustering algorithms when the data set to be clustered is described by a proximity matrix only (relational data) and the number of clusters must be automatically estimated from such data. A fuzzy variant of an evolutionary algorithm for relational clustering is derived and compared against two systematic (pseudo-exhaustive) approaches that can also be used to automatically estimate the number of fuzzy clusters in relational data. An extensive collection of experiments involving 18 artificial and two real data sets is reported and analyzed. (C) 2011 Elsevier B.V. All rights reserved.

Isostructural M(RL)(2)(hfac)(2) complexes with RL=5-(4-[N-tert-butyl-N-aminoxyl]phenyl)pyrimidine

5-(4-(N-tert-Butyl-N-aminoxylphenyl)) pyrimidine (RL, 4PPN) forms crystallographically isostructural and isomorphic pseudo-octahedral M(RL)(2)(hfac)(2) complexes with M(hfac)(2), M = Zn, Cu, Ni, Co, and Mn. Multiple close contacts occur between sites of significant spin density of the organic radical units. Magnetic behavior of the Zn, Cu, Ni, Co complexes appears to involve multiple exchange pathways, with multiple close crystallographic contacts between sites that EPR (of 4PPN) indicates to have observable spin density. Powder EPR spectra at room temperature and low temperature are reported for each complex. Near room temperature, the magnetic moments of the complexes are roughly equal to those expected by a sum of non-interacting moments (two radicals plus ion). As temperature decreases, AFM exchange interactions become evident in all of the complexes. The closest fits to the magnetic data were found for a 1-D Heisenberg AFM chain model in the Zn(II) complex (J/k = (-)7 K), and for three-spin RL-M-RL exchange in the other complexes (J/k = (-)26 K, (-)3 K, (-) 6 K, for Cu(II), Ni(II), and Co(II) complexes, respectively). (C) 2008 Elsevier B.V. All rights reserved.

Normalization procedure for relaxation studies in NMR quantum information processing

NMR quantum information processing studies rely on the reconstruction of the density matrix representing the so-called pseudo-pure states (PPS). An initially pure part of a PPS state undergoes unitary and non-unitary (relaxation) transformations during a computation process, causing a ""loss of purity"" until the equilibrium is reached. Besides, upon relaxation, the nuclear polarization varies in time, a fact which must be taken into account when comparing density matrices at different instants. Attempting to use time-fixed normalization procedures when relaxation is present, leads to various anomalies on matrices populations. On this paper we propose a method which takes into account the time-dependence of the normalization factor. From a generic form for the deviation density matrix an expression for the relaxing initial pure state is deduced. The method is exemplified with an experiment of relaxation of the concurrence of a pseudo-entangled state, which exhibits the phenomenon of sudden death, and the relaxation of the Wigner function of a pseudo-cat state.

A novel MAP-MRF approach for multispectral image contextual classification using combination of suboptimal iterative algorithms

In this paper we present a novel approach for multispectral image contextual classification by combining iterative combinatorial optimization algorithms. The pixel-wise decision rule is defined using a Bayesian approach to combine two MRF models: a Gaussian Markov Random Field (GMRF) for the observations (likelihood) and a Potts model for the a priori knowledge, to regularize the solution in the presence of noisy data. Hence, the classification problem is stated according to a Maximum a Posteriori (MAP) framework. In order to approximate the MAP solution we apply several combinatorial optimization methods using multiple simultaneous initializations, making the solution less sensitive to the initial conditions and reducing both computational cost and time in comparison to Simulated Annealing, often unfeasible in many real image processing applications. Markov Random Field model parameters are estimated by Maximum Pseudo-Likelihood (MPL) approach, avoiding manual adjustments in the choice of the regularization parameters. Asymptotic evaluations assess the accuracy of the proposed parameter estimation procedure. To test and evaluate the proposed classification method, we adopt metrics for quantitative performance assessment (Cohen`s Kappa coefficient), allowing a robust and accurate statistical analysis. The obtained results clearly show that combining sub-optimal contextual algorithms significantly improves the classification performance, indicating the effectiveness of the proposed methodology. (C) 2010 Elsevier B.V. All rights reserved.

NONPERTURBATIVE HQET AT ORDER 1/m

We summarize the first results for masses and decay constants of bottom-strange (pseudo-scalar and vector) mesons from nonperturbatively renormalized heavy-quark effective theory (HQET), using lattice-QCD simulations in the quenched approximation.

Tectonic fabric revealed by AARM of the proterozoic mafic dike swarm in the Salvador city (Bahia state): Sao Francisco Craton, NE Brazil

Magnetic fabric and rock magnetism studies were performed on 25 unmetamorphosed mafic dikes of the Meso-Late Proterozoic (similar to 1.02 Ga) dike swarm from Salvador (Bahia State, NE Brazil). This area lies in the north-eastern part of the Sao Francisco Craton, which was dominantly formed/reworked during the Transamazonian orogeny (2.14-1.94 Ga). The dikes crop out along the beaches and in quarries around Salvador city, and cut across both amphibolite dikes and granulites. Their widths range from a few centimeters up to 30 m with an average of similar to 4 m, and show two main trends N 140-190 and N 100-120 with vertical dips. Magnetic fabrics were determined using both anisotropy of low-field magnetic susceptibility (AMS) and anisotropy of anhysteretic remanent magnetization (AARM). The magnetic mineralogy was investigated by many experiments including remanent magnetization measurements at variable low temperatures (10-300 K), Mossbauer spectroscopy, high temperature magnetization curves (25-700 degrees C) and scanning electron microscopy (SEM). The rock magnetism study suggests pseudo-single-domain magnetite grains carrying the bulk magnetic susceptibility and AARM fabrics. The magnetite grains found in these dikes are large and we discard the presence of single-domain grains. Its composition is close to stoichiometric with low Ti substitution, and its Verwey transition occurs around 120 K. The main AMS fabric recognized in the swarm is so-called normal, in which the K(max)-K(int) plane is parallel to the dike plane and the magnetic foliation pole K(min)) is perpendicular to it. This fabric is interpreted as due to magma flow, and analysis of the K m inclination permitted to infer that approximately 80% of the dikes were fed by horizontal or sub-horizontal flows (K(max) < 30 degrees). This interpretation is supported by structural field evidence found in five dikes. In addition, based on the plunge of K(max), two mantle sources could be inferred; one of them which fed about 80% of the swarm would be located in the southern part of the region, and the other underlied the Valeria quarry. However, for all dikes the AARM tensors are not coaxial with AMS fabrics and show a magnetic lineation (AARM(max)) oriented to N30-60E, suggesting that magnetite grains were rotated clockwise from dike plane. The orientation of AARM lineation is similar to the orientation of a system of faults in which the Salvador normal fault is the most important. These faults were formed during Cretaceous rifting in the Reconcavo-Tucano-jatoba assemblage that corresponds to an aborted intra-continental rift formed during the opening of the South Atlantic. Therefore, the AARM fabric found for the Salvador dikes is probably tectonic in origin and suggests that the dike swarm was affected by the important tectonic event responsible for the break-up of the Gondwanaland. (C) 2008 Elsevier B.V. All rights reserved.