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.

Output sustainability to exogenous and endogenous shocks: evidence from emerging economies

This paper studies the impact of exogenous and endogenous shocks (exogenous shock is used interchangeably with external shock; endogenous shock is used interchangeably with domestic shock) on output fluctuations in post-communist countries during the 2000s. The first part presents the analytical framework and formulates a research hypothesis. The second part presents vector autoregressive estimation and analysis model proposed by Pesaran (2004) and Pesaran and Smith (2006) that relates bank real lending, the cyclical component of output and spreads and accounts for cross-sectional dependence (CD) across the countries. Impulse response functions show that exogenous positive shock lead to a drop in output sustainability for 9 over 12 Central Eastern European countries and Russia, when the endogenous shock is mild and ambiguous. Moreover, the effect of exogenous shock is more significant during the crises. Variance decompositions show that exogenous shock in the aftermath of crisis had a substantial impact on economic activity of emerging economies.

A WAVELET-BASED SPEAKER VERIFICATION ALGORITHM

This paper presents a study on wavelets and their characteristics for the specific purpose of serving as a feature extraction tool for speaker verification (SV), considering a Radial Basis Function (RBF) classifier, which is a particular type of Artificial Neural Network (ANN). Examining characteristics such as support-size, frequency and phase responses, amongst others, we show how Discrete Wavelet Transforms (DWTs), particularly the ones which derive from Finite Impulse Response (FIR) filters, can be used to extract important features from a speech signal which are useful for SV. Lastly, an SV algorithm based on the concepts presented is described.

Do crude oil price changes affect economic growth of India, Pakistan and Bangladesh? : A multivariate time series analysis

This paper analyzes empirically the effect of crude oil price change on the economic growth of Indian-Subcontinent (India, Pakistan and Bangladesh). We use a multivariate Vector Autoregressive analysis followed by Wald Granger causality test and Impulse Response Function (IRF). Wald Granger causality test results show that only India’s economic growth is significantly affected when crude oil price decreases. Impact of crude oil price increase is insignificantly negative for all three countries during first year. In second year, impact is negative but smaller than first year for India, negative but larger for Bangladesh and positive for Pakistan.

Liberalização da conta de capital e fluxos de portfólio para o Brasil

The present work seeks to investigate the dynamics of capital account liberalization and its impact on short run capital flows to Brazil in the period of 1995-2002, considering different segments such as the monetary, derivative and equity markets. This task is pursued by developing a comparative study of financial flows and examining how it is affected by the uncovered interest parity, country risk and the legislation on portfolio capital flows. The empirical framework is based on a vector autoregressive (VAR) analysis using impulse-response functions, variance decomposition and Granger causality tests. In general terms the results indicate a crucial role played by the uncovered interest parity and the country risk to explain portfolio flows, and a less restrictive (more liberalized) legislation is not significant to attract such flows.

Efeitos de política fiscal nos EUA em um modelo FAVAR

O objetivo desse artigo é analisar o impacto da política fiscal sobre diversas variáveis macroeconômicas dos EUA. A metodologia do trabalho empírico baseia-se em um modelo VAR estrutural que incorpora fatores latentes (FAVAR) e para o qual desenvolve-se um esquema de identificação específico. Visto que os fatores são estimados por principal components, estes aproximam-se muito das séries observadas de produção industrial e taxa de juros. Como será visto, este resultado é de fundamental importância para a hipótese de identificação e a escolha dos instrumentos do modelo VAR. Por meio das funções de resposta ao impulso analisa-se os efeitos de um aumento do gasto do governo sobre variáveis de produto e consumo e, por sua vez, corroborando a hipótese de que tanto o PIB quanto as despesas de consumo das famílias aumentam depois desse choque exógeno. Em particular esse efeito sobre o consumo também é verificado quando separamos os indivíduos em várias classes de acordo com renda. Olhando cuidadosamente no entanto pode-se perceber que um aumento no gasto público possui mais impacto sobre os consumidores de renda mais baixa. Ou seja, é provável que por estarem sujeitas a restrições de crédito, as classes mais baixas tem mais dificuldade em suavizar o consumo após um choque agregado.

Estimation of DSGE Models: A Monte Carlo Analysis

Neste trabalho investigamos as propriedades em pequena amostra e a robustez das estimativas dos parâmetros de modelos DSGE. Tomamos o modelo de Smets and Wouters (2007) como base e avaliamos a performance de dois procedimentos de estimação: Método dos Momentos Simulados (MMS) e Máxima Verossimilhança (MV). Examinamos a distribuição empírica das estimativas dos parâmetros e sua implicação para as análises de impulso-resposta e decomposição de variância nos casos de especificação correta e má especificação. Nossos resultados apontam para um desempenho ruim de MMS e alguns padrões de viés nas análises de impulso-resposta e decomposição de variância com estimativas de MV nos casos de má especificação considerados.

The macroeconomics of price adjustments under information frictions and menu costs

Esta tese se dedica ao estudo de modelos de fixação de preços e suas implicações macroeconômicas. Nos primeiros dois capítulos analiso modelos em que as decisões das firmas sobre seus preços praticados levam em conta custos de menu e de informação. No Capítulo 1 eu estimo tais modelos empregando estatísticas de variações de preços dos Estados Unidos, e concluo que: os custos de informação são significativamente maiores que os custos de menu; os dados claramente favorecem o modelo em que informações sobre condições agregadas são custosas enquanto que as idiossincráticas têm custo zero. No Capítulo 2 investigo as consequências de choques monetários e anúncios de desinflação usando os modelos previamente estimados. Mostro que o grau de não-neutralidade monetária é maior no modelo em que parte da informação é grátis. O Capítulo 3 é um artigo em conjunto com Carlos Carvalho (PUC-Rio) e Antonella Tutino (Federal Reserve Bank of Dallas). No artigo examinamos um modelo de fixação de preços em que firmas estão sujeitas a uma restrição de fluxo de informação do tipo Shannon. Calibramos o modelo e estudamos funções impulso-resposta a choques idiossincráticos e agregados. Mostramos que as firmas vão preferir processar informações agregadas e idiossincráticas conjuntamente ao invés de investigá-las separadamente. Este tipo de processamento gera ajustes de preços mais frequentes, diminuindo a persistência de efeitos reais causados por choques monetários.

Credit shocks and monetary policy in Brazil: a structural FAVAR approach

This paper investigates the implications of the credit channel of the monetary policy transmission mechanism in the case of Brazil, using a structural FAVAR (SFAVAR) approach. The term structural comes from the estimation strategy, which generates factors that have a clear economic interpretation. The results show that unexpected shocks in the proxies for the external nance premium and the bank balance sheet channel produce large and persistent uctuations in in ation and economic activity accounting for more than 30% of the error forecast variance of the latter in a three-year horizon. The central bank seems to incorporate developments in credit markets especially variations in credit spreads into its reaction function, as impulse-response exercises show the Selic rate is declining in response to wider credit spreads and a contraction in the volume of new loans. Counterfactual simulations also demonstrate that the credit channel ampli ed the economic contraction in Brazil during the acute phase of the global nancial crisis in the last quarter of 2008, thus gave an important impulse to the recovery period that followed.

The relationships of alternative energies with the technology sector and non-renewable energies

Este trabalho tem como objectivo compreender de que forma os investidores veem as energias renováveis: se as veem como parte do sector tecnológico, à espera de novos desenvolvimentos, ou como uma alternativa aos métodos existentes de produção de energia. Para responder a esta questão, foi desenvolvido um modelo de vectores autoregressivos com quatro variáveis de forma a se poder aplicar um Granger causality test e Impulse Response function. Os resultados sugerem que para o período de 2002-2007 à escala global ambas as hipóteses se confirmam, porém de 2009-2014 os resultados sugerem que os investidores não reconhecem as energias renováveis como um ramo do sector tecnológico, neste período. Para além disso, durante o período de 2009-2014, e quando comparados investidores Americanos com Europeus, os resultados sugerem que apenas o último identifica as energias renováveis como uma fonte viável para a produção energética.

Identification of Mechanical Systems through Kautz Filter

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Forced oscillations with continuum models of atomic force microscopy

The dynamics of the AFM-atomic force microscope follows a model based in a Timoshenko cantilever beam with a tip attached at the free end and acting with the surface of a sample. General boundary conditions arise when the tip is either in contact or non-contact with the surface. The governing equations are given in matrix conservative form subject to localized loads. The eigenanalysis is done with a fundamental matrix response of a damped second-order matrix differential equation. Forced responses are found by using a Galerkin approximation of the matrix impulse response. Simulations results with harmonic and pulse forcing show the filtering character and the effects of the tip-sample interaction at the end of the beam. © 2012 American Institute of Physics.

Digital filtering of oscillations intrinsic to transmission line modeling based on lumped parameters

A correction procedure based on digital signal processing theory is proposed to smooth the numeric oscillations in electromagnetic transient simulation results from transmission line modeling based on an equivalent representation by lumped parameters. The proposed improvement to this well-known line representation is carried out with an Finite Impulse Response (FIR) digital filter used to exclude the high-frequency components associated with the spurious numeric oscillations. To prove the efficacy of this correction method, a well-established frequency-dependent line representation using state equations is modeled with an FIR filter included in the model. The results obtained from the state-space model with and without the FIR filtering are compared with the results simulated by a line model based on distributed parameters and inverse transforms. Finally, the line model integrated with the FIR filtering is also tested and validated based on simulations that include nonlinear and time-variable elements. © 2012 Elsevier Ltd. All rights reserved.