A double data rate (DDR) architecture for OFDM based wireless consumer devices

The creation of OFDM based Wireless Personal Area Networks (WPANs) has allowed the development of high bit-rate wireless communication devices suitable for streaming High Definition video between consumer products, as demonstrated in Wireless-USB and Wireless-HDMI. However, these devices need high frequency clock rates, particularly for the OFDM, FFT and symbol processing sections resulting in high silicon cost and high electrical power. The high clock rates make hardware prototyping difficult and verification is therefore very important but costly. Acknowledging that electrical power in wireless consumer devices is more critical than the number of implemented logic gates, this paper presents a Double Data Rate (DDR) architecture for implementation inside a OFDM baseband codec in order to reduce the high frequency clock rates by a complete factor of 2. The presented architecture has been implemented and tested for ECMA-368 (Wireless- USB context) resulting in a maximum clock rate of 264MHz instead of the expected 528MHz clock rate existing anywhere on the baseband codec die.

A double data rate (DDR) architecture for OFDM based wireless consumer devices

The creation of OFDM based Wireless Personal Area Networks (WPANs) has allowed high bit-rate wireless communication devices suitable for streaming High Definition video between consumer products as demonstrated in Wireless- USB. However, these devices need high clock rates, particularly for the OFDM sections resulting in high silicon cost and high electrical power. Acknowledging that electrical power in wireless consumer devices is more critical than the number of implemented logic gates, this paper presents a Double Data Rate (DDR) architecture to reduce the OFDM input and output clock rate by a factor of 2. The architecture has been implemented and tested for Wireless-USB (ECMA-368) resulting in a maximum clock of 264MHz instead of 528MHz existing anywhere on the die.

The effects of environmental perturbation and measurement error on estimates of the shape parameter in the theta-logistic model of population regulation

The theta-logistic is a widely used generalisation of the logistic model of regulated biological processes which is used in particular to model population regulation. Then the parameter theta gives the shape of the relationship between per-capita population growth rate and population size. Estimation of theta from population counts is however subject to bias, particularly when there are measurement errors. Here we identify factors disposing towards accurate estimation of theta by simulation of populations regulated according to the theta-logistic model. Factors investigated were measurement error, environmental perturbation and length of time series. Large measurement errors bias estimates of theta towards zero. Where estimated theta is close to zero, the estimated annual return rate may help resolve whether this is due to bias. Environmental perturbations help yield unbiased estimates of theta. Where environmental perturbations are large, estimates of theta are likely to be reliable even when measurement errors are also large. By contrast where the environment is relatively constant, unbiased estimates of theta can only be obtained if populations are counted precisely Our results have practical conclusions for the design of long-term population surveys. Estimation of the precision of population counts would be valuable, and could be achieved in practice by repeating counts in at least some years. Increasing the length of time series beyond ten or 20 years yields only small benefits. if populations are measured with appropriate accuracy, given the level of environmental perturbation, unbiased estimates can be obtained from relatively short censuses. These conclusions are optimistic for estimation of theta. (C) 2008 Elsevier B.V All rights reserved.

Exact error estimates and optimal randomized algorithms for integration

Exact error estimates for evaluating multi-dimensional integrals are considered. An estimate is called exact if the rates of convergence for the low- and upper-bound estimate coincide. The algorithm with such an exact rate is called optimal. Such an algorithm has an unimprovable rate of convergence. The problem of existing exact estimates and optimal algorithms is discussed for some functional spaces that define the regularity of the integrand. Important for practical computations data classes are considered: classes of functions with bounded derivatives and Holder type conditions. The aim of the paper is to analyze the performance of two optimal classes of algorithms: deterministic and randomized for computing multidimensional integrals. It is also shown how the smoothness of the integrand can be exploited to construct better randomized algorithms.

A general model of error-prone PCR

In this paper, we generalise a previously-described model of the error-prone polymerase chain reaction (PCR) reaction to conditions of arbitrarily variable amplification efficiency and initial population size. Generalisation of the model to these conditions improves the correspondence to observed and expected behaviours of PCR, and restricts the extent to which the model may explore sequence space for a prescribed set of parameters. Error-prone PCR in realistic reaction conditions is predicted to be less effective at generating grossly divergent sequences than the original model. The estimate of mutation rate per cycle by sampling sequences from an in vitro PCR experiment is correspondingly affected by the choice of model and parameters. (c) 2005 Elsevier Ltd. All rights reserved.

Synchronisation error resistant CDMA detection

A bit-level linear CDMA detector is presented which is based on the minimum variance distortionless response (MVDR) principle. Owing to the interference suppression capability made possible by basing the detector on the MVDR principle and the fact that no inversion of the user correlation matrix is involved, the influence of synchronisation errors is greatly suppressed.

Measuring large topographic change with InSAR: lava thicknesses, extrusion rate and subsidence rate at Santiaguito volcano, Guatemala

Lava flows can produce changes in topography on the order of 10s-100s of metres. A knowledge of the resulting volume change provides evidence about the dynamics of an eruption. We present a method to measure topographic changes from the differential InSAR phase delays caused by the height differences between the current topography and a Digital Elevation Model (DEM). This does not require a pre-event SAR image, so it does not rely on interferometric phase remaining coherent during eruption and emplacement. Synthetic tests predicts that we can estimate lava thickness of as little as �9 m, given a minimum of 5 interferograms with suitably large orbital baseine separations. In the case of continuous motion, such as lava flow subsidence, we invert interferometric phase simultaneously for topographic change and displacement. We demonstrate the method using data from Santiaguito volcano, Guatemala, and measure increases in lava thickness of up to 140 m between 2000 and 2009, largely associated with activity between 2000 and 2005. We find a mean extrusion rate of 0.43 +/- 0.06 m3/s, which lies within the error bounds of the longer term extrusion rate between 1922-2000. The thickest and youngest parts of the flow deposit were shown to be subsiding at an average rate of �-6 cm/yr. This is the first time that flow thickness and subsidence have been measured simultaneously. We expect this method to be suitable for measurment of landslides and other mass flow deposits as well as lava flows.

A multiple error-correction model of housing supply

This paper considers supply dynamics in the context of the Irish residential market. The analysis, in a multiple error-correction framework, reveals that although developers did respond to disequilibrium in supply, the rate of adjustment was relatively slow. In contrast, however, disequilibrium in demand did not impact upon supply, suggesting that inelastic supply conditions could explain the prolonged nature of the boom in the Irish market. Increased elasticity in the later stages of the boom may have been a contributory factor in the extent of the house price falls observed in recent years.

A Double-threshold GARCH Model for the French Franc/Deutschmark exchange rate

This paper combines and generalizes a number of recent time series models of daily exchange rate series by using a SETAR model which also allows the variance equation of a GARCH specification for the error terms to be drawn from more than one regime. An application of the model to the French Franc/Deutschmark exchange rate demonstrates that out-of-sample forecasts for the exchange rate volatility are also improved when the restriction that the data it is drawn from a single regime is removed. This result highlights the importance of considering both types of regime shift (i.e. thresholds in variance as well as in mean) when analysing financial time series.

Forecasting exchange rate volatility using conditional variance models selected by information criteria

This paper uses appropriately modified information criteria to select models from the GARCH family, which are subsequently used for predicting US dollar exchange rate return volatility. The out of sample forecast accuracy of models chosen in this manner compares favourably on mean absolute error grounds, although less favourably on mean squared error grounds, with those generated by the commonly used GARCH(1, 1) model. An examination of the orders of models selected by the criteria reveals that (1, 1) models are typically selected less than 20% of the time.

A variational approach to retrieve rain rate by combining information from rain gauges, radars, and microwave links

Accurate and reliable rain rate estimates are important for various hydrometeorological applications. Consequently, rain sensors of different types have been deployed in many regions. In this work, measurements from different instruments, namely, rain gauge, weather radar, and microwave link, are combined for the first time to estimate with greater accuracy the spatial distribution and intensity of rainfall. The objective is to retrieve the rain rate that is consistent with all these measurements while incorporating the uncertainty associated with the different sources of information. Assuming the problem is not strongly nonlinear, a variational approach is implemented and the Gauss–Newton method is used to minimize the cost function containing proper error estimates from all sensors. Furthermore, the method can be flexibly adapted to additional data sources. The proposed approach is tested using data from 14 rain gauges and 14 operational microwave links located in the Zürich area (Switzerland) to correct the prior rain rate provided by the operational radar rain product from the Swiss meteorological service (MeteoSwiss). A cross-validation approach demonstrates the improvement of rain rate estimates when assimilating rain gauge and microwave link information.

An idealized study of coupled atmosphere-ocean 4D-Var in the presence of model error

Atmosphere only and ocean only variational data assimilation (DA) schemes are able to use window lengths that are optimal for the error growth rate, non-linearity and observation density of the respective systems. Typical window lengths are 6-12 hours for the atmosphere and 2-10 days for the ocean. However, in the implementation of coupled DA schemes it has been necessary to match the window length of the ocean to that of the atmosphere, which may potentially sacrifice the accuracy of the ocean analysis in order to provide a more balanced coupled state. This paper investigates how extending the window length in the presence of model error affects both the analysis of the coupled state and the initialized forecast when using coupled DA with differing degrees of coupling. Results are illustrated using an idealized single column model of the coupled atmosphere-ocean system. It is found that the analysis error from an uncoupled DA scheme can be smaller than that from a coupled analysis at the initial time, due to faster error growth in the coupled system. However, this does not necessarily lead to a more accurate forecast due to imbalances in the coupled state. Instead coupled DA is more able to update the initial state to reduce the impact of the model error on the accuracy of the forecast. The effect of model error is potentially most detrimental in the weakly coupled formulation due to the inconsistency between the coupled model used in the outer loop and uncoupled models used in the inner loop.

A device to improve the Schleger and Turner method for sweating rate measurements

The objective of this study was to test a device developed to improve the functionality, accuracy and precision of the original technique for sweating rate measurements proposed by Schleger and Turner [Schleger AV, Turner HG (1965) Aust J Agric Res 16:92-106]. A device was built for this purpose and tested against the original Schleger and Turner technique. Testing was performed by measuring sweating rates in an experiment involving six Mertolenga heifers subjected to four different thermal levels in a climatic chamber. The device exhibited no functional problems and the results obtained with its use were more consistent than with the Schleger and Turner technique. There was no difference in the reproducibility of the two techniques (same accuracy), but measurements performed with the new device had lower repeatability, corresponding to lower variability and, consequently, to higher precision. When utilizing this device, there is no need for physical contact between the operator and the animal to maintain the filter paper discs in position. This has important advantages: the animals stay quieter, and several animals can be evaluated simultaneously. This is a major advantage because it allows more measurements to be taken in a given period of time, increasing the precision of the observations and diminishing the error associated with temporal hiatus (e.g., the solar angle during field studies). The new device has higher functional versatility when taking measurements in large-scale studies (many animals) under field conditions. The results obtained in this study suggest that the technique using the device presented here could represent an advantageous alternative to the original technique described by Schleger and Turner.

What happens after the central bank of Brazil increases the target interbank rate by 1%?

I start presenting an explicit solution to Taylorís (2001) model, in order to illustrate the link between the target interest rate and the overnight interest rate prevailing in the economy. Next, I use Vector Auto Regressions to shed some light on the evolution of key macroeconomic variables after the Central Bank of Brazil increases the target interest rate by 1%. Point estimates show a four-year accumulated output loss ranging from 0:04% (whole sample, 1980 : 1-2004 : 2; quarterly data) to 0:25% (Post-Real data only) with a Örst-year peak output response between 0:04% and 1:0%; respectively. Prices decline between 2% and 4% in a 4-year horizon. The accumulated output response is found to be between 3:5 and 6 times higher after the Real Plan than when the whole sample is considered. The 95% confidence bands obtained using bias-corrected bootstrap always include the null output response when the whole sample is used, but not when the data is restricted to the Post-Real period. Innovations to interest rates explain between 4:9% (whole sample) and 9:2% (post-Real sample) of the forecast error of GDP.

Exchange rate dynamics in Brazil

The paper aims to investigate on empirical and theoretical grounds the Brazilian exchange rate dynamics under floating exchange rates. The empirical analysis examines the short and long term behavior of the exchange rate, interest rate (domestic and foreign) and country risk using econometric techniques such as variance decomposition, Granger causality, cointegration tests, error correction models, and a GARCH model to estimate the exchange rate volatility. The empirical findings suggest that one can argue in favor of a certain degree of endogeneity of the exchange rate and that flexible rates have not been able to insulate the Brazilian economy in the same patterns predicted by literature due to its own specificities (managed floating with the use of international reserves and domestic interest rates set according to inflation target) and to externally determined variables such as the country risk. Another important outcome is the lack of a closer association of domestic and foreign interest rates since the new exchange regime has been adopted. That is, from January 1999 to May 2004, the US monetary policy has no significant impact on the Brazilian exchange rate dynamics, which has been essentially endogenous primarily when we consider the fiscal dominance expressed by the probability of default.