Low-complexity iterative method of equalization for single carrier with cyclic prefix in doubly selective channels

Orthogonal frequency division multiplexing (OFDM) requires an expensive linear amplifier at the transmitter due to its high peak-to-average power ratio (PAPR). Single carrier with cyclic prefix (SC-CP) is a closely related transmission scheme that possesses most of the benefits of OFDM but does not have the PAPR problem. Although in a multipath environment, SC-CP is very robust to frequency-selective fading, it is sensitive to the time-selective fading characteristics of the wireless channel that disturbs the orthogonality of the channel matrix (CM) and increases the computational complexity of the receiver. In this paper, we propose a time-domain low-complexity iterative algorithm to compensate for the effects of time selectivity of the channel that exploits the sparsity present in the channel convolution matrix. Simulation results show the superior performance of the proposed algorithm over the standard linear minimum mean-square error (L-MMSE) equalizer for SC-CP.

On the Performance of Eigenvalue-Based Cooperative Spectrum Sensing for Cognitive Radio

In this paper, the distribution of the ratio of extreme eigenvalues of a complex Wishart matrix is studied in order to calculate the exact decision threshold as a function of the desired probability of false alarm for the maximum-minimum eigenvalue (MME) detector. In contrast to the asymptotic analysis reported in the literature, we consider a finite number of cooperative receivers and a finite number of samples and derive the exact decision threshold for the probability of false alarm. The proposed exact formulation is further reduced to the case of two receiver-based cooperative spectrum sensing. In addition, an approximate closed-form formula of the exact threshold is derived in terms of a desired probability of false alarm for a special case having equal number of receive antennas and signal samples. Finally, the derived analytical exact decision thresholds are verified with Monte-Carlo simulations. We show that the probability of detection performance using the proposed exact decision thresholds achieves significant performance gains compared to the performance of the asymptotic decision threshold.

Structural similarity of directed universal hierarchical graphs: A low computational complexity approach

In the present paper we mainly introduce an efficient approach to measure the structural similarity of so called directed universal hierarchical graphs. We want to underline that directed universal hierarchical graphs can be obtained from generalized trees which are already introduced. In order to classify these graphs, we state our novel graph similarity method. As a main result we notice that our novel algorithm has low computational complexity. (c) 2007 Elsevier Inc. All rights reserved.

Evidence-based Practice in Cognitive-Behaviour Therapy

book review

Predicting community responses to perturbations in the face of imperfect knowledge and network complexity

How best to predict the effects of perturbations to ecological communities has been a long-standing goal for both applied and basic ecology. This quest has recently been revived by new empirical data, new analysis methods, and increased computing speed, with the promise that ecologically important insights may be obtainable from a limited knowledge of community interactions. We use empirically based and simulated networks of varying size and connectance to assess two limitations to predicting perturbation responses in multispecies communities: (1) the inaccuracy by which species interaction strengths are empirically quantified and (2) the indeterminacy of species responses due to indirect effects associated with network size and structure. We find that even modest levels of species richness and connectance (similar to 25 pairwise interactions) impose high requirements for interaction strength estimates because system indeterminacy rapidly overwhelms predictive insights. Nevertheless, even poorly estimated interaction strengths provide greater average predictive certainty than an approach that uses only the sign of each interaction. Our simulations provide guidance in dealing with the trade-offs involved in maximizing the utility of network approaches for predicting dynamics in multispecies communities.

Scaling of Food-Web Properties with Diversity and Complexity Across Ecosystems

Trophic scaling models describe how topological food-web properties such as the number of predator prey links scale with species richness of the community. Early models predicted that either the link density (i.e. the number of links per species) or the connectance (i.e. the linkage probability between any pair of species) is constant across communities. More recent analyses, however, suggest that both these scaling models have to be rejected, and we discuss several hypotheses that aim to explain the scale dependence of these complexity parameters. Based on a recent, highly resolved food-web compilation, we analysed the scaling behaviour of 16 topological parameters and found significant power law scaling relationships with diversity (i.e. species richness) and complexity (i.e. connectance) for most of them. These results illustrate the lack of universal constants in food-web ecology as a function of diversity or complexity. Nonetheless, our power law scaling relationships suggest that fundamental processes determine food-web topology, and subsequent analyses demonstrated that ecosystem-specific differences in these relationships were of minor importance. As such, these newly described scaling relationships provide robust and testable cornerstones for future structural food-web models.

ON THE MOLECULAR COMPLEXITY OF THE HOT CORES IN ORION-A - GRAIN SURFACE-CHEMISTRY AS THE LAST REFUGE OF THE SCOUNDREL

We have modeled the gas phase chemistry of warm molecular material around protostars that is seeded with evaporating grain mantles. We show that the release of simple molecules into the gas drives ion-molecule and neutral chemistries which can account for many of the complex 0-bearing and N-bearing molecules observed in hot cores. Initial grain mantle components and secondary product molecules are identified, and the observational consequences are discussed.

Genetic variation in the interleukin-1 beta-converting enzyme associates with cognitive function. The PROSPER study

Inflammation is thought to play an important role in the development of cognitive decline and dementia in old age. The interleukin-1 signalling pathway may play a prominent role in this process. The gene encoding for interleukin-1 beta-converting enzyme (ICE) is likely to influence IL-1 beta levels. Inhibition of ICE decreases the age-related increase in IL-1 beta levels and may therefore improve memory function. We assessed whether genetic variation in the ICE gene associates with cognitive function in an elderly population. All 5804 participants of the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) were genotyped for the 10643GC, 9323GA, 8996AG and 5352GA polymorphisms in the ICE gene. Cross-sectional associations between the polymorphisms and cognitive function were assessed with linear regression. Longitudinal associations between polymorphisms, haplotypes and cognitive function were assessed with linear mixed models. All associations were adjusted for sex, age, education, country, treatment with pravastatin and version of test where appropriate. Subjects carrying the variants 10643C and 5352A allele had significantly lower IL-1 beta production levels (P