Increasing the speed of parallel decoding of turbo codes

Turbo codes experience a significant decoding delay because of the iterative nature of the decoding algorithms, the high number of metric computations and the complexity added by the (de)interleaver. The extrinsic information is exchanged sequentially between two Soft-Input Soft-Output (SISO) decoders. Instead of this sequential process, a received frame can be divided into smaller windows to be processed in parallel. In this paper, a novel parallel processing methodology is proposed based on the previous parallel decoding techniques. A novel Contention-Free (CF) interleaver is proposed as part of the decoding architecture which allows using extrinsic Log-Likelihood Ratios (LLRs) immediately as a-priori LLRs to start the second half of the iterative turbo decoding. The simulation case studies performed in this paper show that our parallel decoding method can provide %80 time saving compared to the standard decoding and %30 time saving compared to the previous parallel decoding methods at the expense of 0.3 dB Bit Error Rate (BER) performance degradation.

Territories of scarcity and creativity: a critical view of informal settlements and emerging tactics under conditions of scarcity in Nairobi, Kenya and Quito, Ecuador

This thesis explores the processes through which scarcity is constructed in informal settlements and how conditions emerging within its limits gives way to particular socio-spatial phenomena and influence the emergence of self-organisation and creative strategies from a non-expert perspective. At the same time, this thesis deconstructs these emerging tactics (reactive and transformative) in a diagrammatic way to generate a critical study of their potential for socio-spatial change that goes beyond the everyday survival. Most people associate scarcity with “not having enough” of something, most usually of a material nature. In contrast, this paper is based on the premise that scarcity is a constructed condition, therefore exploring it beyond its immediate manifestation and illustrating its discursive, distributive and socio-material components. In this line, the research uses Assemblage Theory as both an approach and a tool for analysis. This approach allows the research to depart from everyday narratives of the residents, and gradually evolve into a multi-scalar, non-linear reading of scarcity, by following leads into different realms and unpacking a series of routine events to uncover their connections to wider processes and particular elements affecting the settlement and the city as a whole. For this purpose, the research is based on a qualitative, flexible and multi-sited methodology, using different case studies as testing grounds. Collected data stems from a 11-months ethnographic fieldwork in informal settlements in Ecuador and Kenya, analysing the socio-spatial practices and strategies deployed by the different actors producing the built environment and arising from everyday and latent experiences of scarcity. The thesis examines the multi-scalar nature of these strategies, including self-building and management tactics, the mobilisation of grassroots organisations, the innovative ways of collaborating deployed by different coalitions and the reformulation of urban development policies. As outcomes of the research, the thesis will show illustrative diagrams that allow a better understanding of, firstly, the construction of scarcity in the built environment beyond its immediate manifestation and secondly, the way that emerging tactics a) improve existing conditions of scarcity, b) reinforce the status quo or c) contribute to the worsening of the original condition. Therefore, this thesis aims to offer lessons with both practical and theoretical considerations, by firstly, giving an insight into the complexity and transcalar nature of the construction of scarcity in informal settlements; secondly, by illustrating how acute conditions related to scarcity gives birth to a plethora of particular phenomena shaping the territory, social relationships and processes; and thirdly, by identifying specific characteristics within the informal that might allow for new readings of the city and possibilities for socio-spatial change under conditions of scarcity.

3D Reconstruction of Medical Images from Slices Automatically Landmarked with Growing Neural Models

In this study, we utilise a novel approach to segment out the ventricular system in a series of high resolution T1-weighted MR images. We present a brain ventricles fast reconstruction method. The method is based on the processing of brain sections and establishing a fixed number of landmarks onto those sections to reconstruct the ventricles 3D surface. Automated landmark extraction is accomplished through the use of the self-organising network, the growing neural gas (GNG), which is able to topographically map the low dimensionality of the network to the high dimensionality of the contour manifold without requiring a priori knowledge of the input space structure. Moreover, our GNG landmark method is tolerant to noise and eliminates outliers. Our method accelerates the classical surface reconstruction and filtering processes. The proposed method offers higher accuracy compared to methods with similar efficiency as Voxel Grid.

Multivariate Moments Expansion Density: Application of the Dynamic Equicorrelation Model

In this study, we propose a new semi-nonparametric (SNP) density model for describing the density of portfolio returns. This distribution, which we refer to as the multivariate moments expansion (MME), admits any non-Gaussian (multivariate) distribution as its basis because it is specified directly in terms of the basis density’s moments. To obtain the expansion of the Gaussian density, the MME is a reformulation of the multivariate Gram-Charlier (MGC), but the MME is much simpler and tractable than the MGC when positive transformations are used to produce well-defined densities. As an empirical application, we extend the dynamic conditional equicorrelation (DECO) model to an SNP framework using the MME. The resulting model is parameterized in a feasible manner to admit two-stage consistent estimation and it represents the DECO as well as the salient non-Gaussian features of portfolio return distributions. The in- and out-of-sample performance of a MME-DECO model of a portfolio of 10 assets demonstrate that it can be a useful tool for risk management purposes.