Calculus of variations on time scales and discrete fractional calculus

Estudamos problemas do cálculo das variações e controlo óptimo no contexto das escalas temporais. Especificamente, obtemos condições necessárias de optimalidade do tipo de Euler–Lagrange tanto para lagrangianos dependendo de derivadas delta de ordem superior como para problemas isoperimétricos. Desenvolvemos também alguns métodos directos que permitem resolver determinadas classes de problemas variacionais através de desigualdades em escalas temporais. No último capítulo apresentamos operadores de diferença fraccionários e propomos um novo cálculo das variações fraccionário em tempo discreto. Obtemos as correspondentes condições necessárias de Euler– Lagrange e Legendre, ilustrando depois a teoria com alguns exemplos.

Fractional calculus on time scales - Cálculo fraccional em escalas temporais

Introduzimos um cálculo das variações fraccional nas escalas temporais ℤ e (hℤ)!. Estabelecemos a primeira e a segunda condição necessária de optimalidade. São dados alguns exemplos numéricos que ilustram o uso quer da nova condição de Euler–Lagrange quer da nova condição do tipo de Legendre. Introduzimos também novas definições de derivada fraccional e de integral fraccional numa escala temporal com recurso à transformada inversa generalizada de Laplace.

Study of sewage sludge aimed at agricultural soil amendment by thermogravimetric analysis and fourier-transform infrared spectroscopy

Thermal degradation and gaseous products evolving from the pyrolysis of sewage sludge, aimed at agricultural soil amendment, were investigated using Thermogravimetric Analysis in conjunction with Fourier Transform Infrared Analysis (TG-FTIR). The materials were studied in temperatures ranging from 30 to 800 ºC. Furthermore infrared spectra of sewage sludge samples were performed as a complementary technique. In parallel the sewage sludge was spiked with ibuprofen in order to test whether the mentioned techniques are able to detect the drug. Thermal analysis showed the range of 200-400ºC as the most characteristic for weight loss, corresponding with the organic matter volatilization, while the range of 500-800ºC was also characteristic and due to the volatilization of carbonates. On the other hand, ibuprofen-spiking tests identified at temperature range (150-250ºC) where the compound totally volatilizes, therefore, in this work, the detection of ibuprofen by TGA was established for concentrations higher than 0.5 g/kg sludge, concentration 102 times higher than the concentrations measured by other authors in regular sewage sludge (Martín, et al., 2010). A correlation has been found between the ibuprofen concentrations in the sludge and the intensity of the absorption bands, both for FT-IR spectra at the maximum emission temperature for ibuprofen (232ºC) as for the FT-IR spectra of the non-pyrolyzed samples.

An extensible complex fast Fourier transform processor chip for real-time spectrum analysis and measurement

This paper describes in detail the design of a CMOS custom fast Fourier transform (FFT) processor for computing a 256-point complex FFT. The FFT is well-suited for real-time spectrum analysis in instrumentation and measurement applications. The FFT butterfly processor reported here consists of one parallel-parallel multiplier and two adders. It is capable of computing one butterfly computation every 100 ns thus it can compute a 256-point complex FFT in 102.4 μs excluding data input and output processes.

Forecasting overseas visitors into the United Kingdom using continuous time and autoregressive fractional integrated moving average models with discrete data

This paper applies Gaussian estimation methods to continuous time models for modelling overseas visitors into the UK. The use of continuous time modelling is widely used in economics and finance but not in tourism forecasting. Using monthly data for 1986–2010, various continuous time models are estimated and compared to autoregressive integrated moving average (ARIMA) and autoregressive fractionally integrated moving average (ARFIMA) models. Dynamic forecasts are obtained over different periods. The empirical results show that the ARIMA model performs very well, but that the constant elasticity of variance (CEV) continuous time model has the lowest root mean squared error (RMSE) over a short period.

Discrete Gaussian Sampling for Low-Power Devices

Thesis (Master's)--University of Washington, 2015

Inflation targeting and the consistency of monetary policy decisions in Mexico: an empirical analysis with discrete choice models

This paper examines the nature of monetary policy decisions in Mexico using discrete choice models applied to the Central Bank's explicit monetary policy instrument. We find that monetary policy adjustments in Mexico have been strongly consistent with the CB's inflation targeting strategy. We also find evidence that monetary policy responds in a forward-looking manner to deviations of inflation from the target and that observed policy adjustments exhibit asymmetric features, with stronger responses to positive than to negative deviations of inflation from the target and a greater likelihood of policy persistence during periods when monetary policy is tightened, compared with periods when policy is loosened.

A Novel Sub-Nyquist Fourier Transform Estimator Based on Alias-free Hybrid Stratified Sampling

This paper introduces a novel method of estimating theFourier transform of deterministic continuous-time signals from a finite number N of their nonuniformly spaced measurements. These samples, located at a mixture of deterministic and random time instants, are collected at sub-Nyquist rates since no constraints are imposed on either the bandwidth or the spectral support of the processed signal. It is shown that the proposed estimation approach converges uniformly for all frequencies at the rate N^−5 or faster. This implies that it significantly outperforms its alias-free-sampling-based predecessors, namely stratified and antithetical stratified estimates, which are shown to uniformly convergence at a rate of N^−1. Simulations are presented to demonstrate the superior performance and low complexity of the introduced technique.

Application of continuous wavelet transform to the analysis of the modulus of the fractional Fourier transform bands for resolving two component mixture

In this paper, the fractional Fourier transform (FrFT) is applied to the spectral bands of two component mixture containing oxfendazole and oxyclozanide to provide the multicomponent quantitative prediction of the related substances. With this aim in mind, the modulus of FrFT spectral bands are processed by the continuous Mexican Hat family of wavelets, being denoted by MEXH-CWT-MOFrFT. Four modulus sets are obtained for the parameter a of the FrFT going from 0.6 up to 0.9 in order to compare their effects upon the spectral and quantitative resolutions. Four linear regression plots for each substance were obtained by measuring the MEXH-CWT-MOFrFT amplitudes in the application of the MEXH family to the modulus of the FrFT. This new combined powerful tool is validated by analyzing the artificial samples of the related drugs, and it is applied to the quality control of the commercial veterinary samples.

Analysis of financial indices by means of the windowed Fourier transform

The goal of this study is to analyze the dynamical properties of financial data series from nineteen worldwide stock market indices (SMI) during the period 1995–2009. SMI reveal a complex behavior that can be explored since it is available a considerable volume of data. In this paper is applied the window Fourier transform and methods of fractional calculus. The results reveal classification patterns typical of fractional order systems.

Analysis of financial data series using fractional Fourier transform and multidimensional scaling

The goal of this study is the analysis of the dynamical properties of financial data series from worldwide stock market indexes during the period 2000–2009. We analyze, under a regional criterium, ten main indexes at a daily time horizon. The methods and algorithms that have been explored for the description of dynamical phenomena become an effective background in the analysis of economical data. We start by applying the classical concepts of signal analysis, fractional Fourier transform, and methods of fractional calculus. In a second phase we adopt the multidimensional scaling approach. Stock market indexes are examples of complex interacting systems for which a huge amount of data exists. Therefore, these indexes, viewed from a different perspectives, lead to new classification patterns.

Optimal approximation of fractional derivatives through discrete-time fractions using genetic algorithms

This study addresses the optimization of rational fraction approximations for the discrete-time calculation of fractional derivatives. The article starts by analyzing the standard techniques based on Taylor series and Padé expansions. In a second phase the paper re-evaluates the problem in an optimization perspective by tacking advantage of the flexibility of the genetic algorithms.

Automated design of microwave discrete tuning differential capacitance circuits in Si-integrated technologies

A genetic algorithm used to design radio-frequency binary-weighted differential switched capacitor arrays (RFDSCAs) is presented in this article. The algorithm provides a set of circuits all having the same maximum performance. This article also describes the design, implementation, and measurements results of a 0.25 lm BiCMOS 3-bit RFDSCA. The experimental results show that the circuit presents the expected performance up to 40 GHz. The similarity between the evolutionary solutions, circuit simulations, and measured results indicates that the genetic synthesis method is a very useful tool for designing optimum performance RFDSCAs.

Automated synthesis procedure of RF discrete tuning differential capacitance circuits

The paper presents a RFDSCA automated synthesis procedure. This algorithm determines several RFDSCA circuits from the top-level system specifications all with the same maximum performance. The genetic synthesis tool optimizes a fitness function proportional to the RFDSCA quality factor and uses the epsiv-concept and maximin sorting scheme to achieve a set of solutions well distributed along a non-dominated front. To confirm the results of the algorithm, three RFDSCAs were simulated in SpectreRF and one of them was implemented and tested. The design used a 0.25 mum BiCMOS process. All the results (synthesized, simulated and measured) are very close, which indicate that the genetic synthesis method is a very useful tool to design optimum performance RFDSCAs.