The κ− μ / Inverse Gamma Fading Model

Statistical distributions have been extensively used in modeling fading effects in conventional and modern wireless communications. In the present work, we propose a novel κ − µ composite shadowed fading model, which is based on the valid assumption that the mean signal power follows the inverse gamma distribution instead of the lognormal or commonly used gamma distributions. This distribution has a simple relationship with the gamma distribution, but most importantly, its semi heavy-tailed characteristics constitute it suitable for applications relating to modeling of shadowed fading. Furthermore, the derived probability density function of the κ − µ / inverse gamma composite distribution admits a rather simple algebraic representation that renders it convenient to handle both analytically and numerically. The validity and utility of this fading model are demonstrated by means of modeling the fading effects encountered in body centric communications channels, which have been known to be susceptible to the shadowing effect. To this end, extensive comparisons are provided between theoretical and respective real-time measurement results. It is shown that these comparisons exhibit accurate fitting of the new model for various measurement set ups that correspond to realistic communication scenarios.

The η − µ / Inverse Gamma Composite Fading Model

In this paper we propose a new composite fadingmodel which assumes that the mean signal power of an η−µ signalenvelope follows an inverse gamma distribution. The inversegamma distribution has a simple relationship with the gammadistribution and can be used to model shadowed fading due to itssemi heavy-tailed characteristics. To demonstrate the utility of thenew η−µ / inverse gamma composite fading model, we investigatethe characteristics of the shadowed fading behavior observed inbody centric communications channels which are known to besusceptible to shadowing effects, particularly generated by thehuman body. It is shown that the η−µ / inverse gamma compositefading model provided an excellent fit to the measurement data.Moreover, using Kullback-Leibler divergence, the η −µ / inversegamma composite fading model was found to provide a better fitto the measured data than the κ − µ / inverse gamma compositefading model, for the communication scenarios considered here.

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.

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.

Uncertainty propagation in inverse reliability-based design of composite structures

An approach for the analysis of uncertainty propagation in reliability-based design optimization of composite laminate structures is presented. Using the Uniform Design Method (UDM), a set of design points is generated over a domain centered on the mean reference values of the random variables. A methodology based on inverse optimal design of composite structures to achieve a specified reliability level is proposed, and the corresponding maximum load is outlined as a function of ply angle. Using the generated UDM design points as input/output patterns, an Artificial Neural Network (ANN) is developed based on an evolutionary learning process. Then, a Monte Carlo simulation using ANN development is performed to simulate the behavior of the critical Tsai number, structural reliability index, and their relative sensitivities as a function of the ply angle of laminates. The results are generated for uniformly distributed random variables on a domain centered on mean values. The statistical analysis of the results enables the study of the variability of the reliability index and its sensitivity relative to the ply angle. Numerical examples showing the utility of the approach for robust design of angle-ply laminates are presented.

Fractional-order impulse response of the respiratory system

This paper presents the measurement, frequency-response modeling and identification, and the corresponding impulse time response of the human respiratory impedance and admittance. The investigated adult patient groups were healthy, diagnosed with chronic obstructive pulmonary disease and kyphoscoliosis, respectively. The investigated children patient groups were healthy, diagnosed with asthma and cystic fibrosis, respectively. Fractional order (FO) models are identified on the measured impedance to quantify the respiratory mechanical properties. Two methods are presented for obtaining and simulating the time-domain impulse response from FO models of the respiratory admittance: (i) the classical pole-zero interpolation proposed by Oustaloup in the early 90s, and (ii) the inverse discrete Fourier Transform (DFT). The results of the identified FO models for the respiratory admittance are presented by means of their average values for each group of patients. Consequently, the impulse time response calculated from the frequency response of the averaged FO models is given by means of the two methods mentioned above. Our results indicate that both methods provide similar impulse response data. However, we suggest that the inverse DFT is a more suitable alternative to the high order transfer functions obtained using the classical Oustaloup filter. Additionally, a power law model is fitted on the impulse response data, emphasizing the intrinsic fractal dynamics of the respiratory system.

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.

Simulation and dynamics of freeway traffic

This paper presents the new package entitled Simulator of Intelligent Transportation Systems (SITS) and a computational oriented analysis of traffic dynamics. The SITS adopts a microscopic simulation approach to reproduce real traffic conditions considering different types of vehicles, drivers and roads. A set of experiments with the SITS reveal the dynamic phenomena exhibited by this kind of system. For this purpose a modelling formalism is developed that embeds the statistics and the Laplace transform. The results make possible the adoption of classical system theory tools and point out that it is possible to study traffic systems taking advantage of the knowledge gathered with automatic control algorithms. A complementary perspective for the analysis of the traffic flow is also quantified through the entropy measure.

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.