A ressonância estocástica (RE) mostra que certos níveis de ruído ajudam na detecção e transmissão de sinais subliminares. Melhorias no desempenho do sistema somato-sensorial e motor (dentre outros) têm sido obtidos por meio da RE gerada pela utilização de sinais aditivos de intensidade ótima. O sinal aditivo (SA) mais comumente utilizado é o ruído branco gaussiano (RBG). Este estudo teve como objetivo verificar se é possível gerar RE no sistema sensorial tátil usando como SA um sinal senoidal e comparar estes resultados com os obtidos realizando o mesmo experimento com SA de tipo RBG. Os sinais usados no experimento foram definidos como sinal de estímulo (SE) de 3Hz a ser reconhecido com a ajuda dos SA, sinal aditivo senoidal (SAS) de 150Hz e sinal aditivo de ruido branco gaussiano (SARBG) filtrado a 150Hz. Na primeira parte do estudo foi feita uma simulação do modelo de neurônio de Hodgkin e Huxley para verificar se na teoria podia se obter RE para SE e SA senoidais. Foi injetado um sinal senoidal de 3Hz no modelo com uma intensidade para a qual o neurônio não conseguia gerar potencial de ação (PA). Quando a este sinal inicial foi adicionado um sinal senoidal de frequência superior, o neurônio conseguiu responder. A mesma resposta foi obtida quando o SA usado foi RBG, conseguindo mostrar de forma qualitativa a nossa hipótese a partir de um modelo simulado. Posteriormente foi realizado um estudo psicofísico com 20 voluntários (11 homens e 9 mulheres) para verificar o desempenho do SAS e comparar este com o desempenho de SARBG para a detecção sensorial do SE. Primeiro foi achado o limiar de detecção (LD) para cada um dos sinais usados e no experimento este valor foi usado para determinar a intensidade de estímulo. No caso do SE a intensidade foi definida como 80% do LD de cada voluntário. No caso dos SA a intensidade foi variando entre 0% até 80% do LD, com o objetivo de se encontrar a melhor proporção de SA adicionado para detectar o SE. Em 90% dos casos conseguiu-se gerar RE tanto empregando um sinal senoidal de frequência rápida como SA, quanto utilizando-se RBG. Ambos SAs apresentaram uma melhoria estatisticamente significativa na proporção de detecção (PD) do SE. Porém, nenhum dos SA apresentou um melhor desempenho em relação ao outro, de maneira que poderia ser usado tanto um quanto outro tipo de SA para gerar RE no sistema somato-sensorial. Este trabalho é pioneiro em usar uma combinação de senóides para gerar RE e abre as portas à elaboração e desenvolvimento de dispositivos biomédicos que contenham uma parte geradora de RE e consigam melhorar a estabilidade e controle postural em pessoas com deficiência motora ou somato-sensorial. / Stochastic ressonance (SR) shows that certain levels of noise help to detect and transmit subliminal signals. Improvements in the performance of the somatosensory and motor systems (among others) have been obtained through the SR generated using additive signals with optimal intensity. The most commonly used additive signal (AS) is white Gaussian noise (WGN). This study aimed to verify whether it is possible to generate SR in the tactile sensory system using a sinusoidal signal as the AS and, at the same time, compare the results when the AS was WGN. The signals used in the experiments were defined as 3Hz for the stimulus signal (SS), to be recognized with the aid of ASs. These were either a sinuoid of 150Hz additive sinusoidal signal (ASS) or a white Gaussian noise additive signal (WGNAS) filtered at 150Hz. In the first part of the study a simulation of the Hodgkin and Huxley neuron model was made to verify if it could undergo SR for the same types of SS and AS mentioned before. A 3Hz sine signal was injected into the model with an intensity at which the neuron could not generate action potentials. When a higher frequency sine wave was added to this initial signal, the neuron could respond. The same behaviour was obtained when the additive signal used was WGN, giving, hence, a qualitative confirmation of our hypothesis. A psychophysical study was then carried out with 20 volunteers (11 men and 9 women) to verify the performance of the ASS and compare it with the WGNAS for the sensory detection of the sinusoidal SS. Initially, the detection threshold (DT) was found for each of the signals used. During the experiment, this value was used to determine the stimulus intensity. In the case of the SS the intensity was defined as 80 % of the DT of each volunteer. In the case of ASs, the intensity varied from 0% to 80% of the DT, in order to find the best proportion of AS added to detect the SS. In 90% of the cases it was possible to generate SR using either a fast frequency ASS or the WGNAS. Both ASs showed a statistically significant improvement in the detection rate (DR) of the SS. However, none of ASs performed better than the other, so that both types could be used to generate SR in the somatosensory system. This work has pioneered the use of a combination of sinusoids to generate SR and opens the door to the development of biomedical devices that help generate SR to provide stability improvement and better postural control for people with motor or somatosensory impairment.

A ressonância estocástica (RE) mostra que certos níveis de ruído ajudam na detecção e transmissão de sinais subliminares. Melhorias no desempenho do sistema somato-sensorial e motor (dentre outros) têm sido obtidos por meio da RE gerada pela utilização de sinais aditivos de intensidade ótima. O sinal aditivo (SA) mais comumente utilizado é o ruído branco gaussiano (RBG). Este estudo teve como objetivo verificar se é possível gerar RE no sistema sensorial tátil usando como SA um sinal senoidal e comparar estes resultados com os obtidos realizando o mesmo experimento com SA de tipo RBG. Os sinais usados no experimento foram definidos como sinal de estímulo (SE) de 3Hz a ser reconhecido com a ajuda dos SA, sinal aditivo senoidal (SAS) de 150Hz e sinal aditivo de ruido branco gaussiano (SARBG) filtrado a 150Hz. Na primeira parte do estudo foi feita uma simulação do modelo de neurônio de Hodgkin e Huxley para verificar se na teoria podia se obter RE para SE e SA senoidais. Foi injetado um sinal senoidal de 3Hz no modelo com uma intensidade para a qual o neurônio não conseguia gerar potencial de ação (PA). Quando a este sinal inicial foi adicionado um sinal senoidal de frequência superior, o neurônio conseguiu responder. A mesma resposta foi obtida quando o SA usado foi RBG, conseguindo mostrar de forma qualitativa a nossa hipótese a partir de um modelo simulado. Posteriormente foi realizado um estudo psicofísico com 20 voluntários (11 homens e 9 mulheres) para verificar o desempenho do SAS e comparar este com o desempenho de SARBG para a detecção sensorial do SE. Primeiro foi achado o limiar de detecção (LD) para cada um dos sinais usados e no experimento este valor foi usado para determinar a intensidade de estímulo. No caso do SE a intensidade foi definida como 80% do LD de cada voluntário. No caso dos SA a intensidade foi variando entre 0% até 80% do LD, com o objetivo de se encontrar a melhor proporção de SA adicionado para detectar o SE. Em 90% dos casos conseguiu-se gerar RE tanto empregando um sinal senoidal de frequência rápida como SA, quanto utilizando-se RBG. Ambos SAs apresentaram uma melhoria estatisticamente significativa na proporção de detecção (PD) do SE. Porém, nenhum dos SA apresentou um melhor desempenho em relação ao outro, de maneira que poderia ser usado tanto um quanto outro tipo de SA para gerar RE no sistema somato-sensorial. Este trabalho é pioneiro em usar uma combinação de senóides para gerar RE e abre as portas à elaboração e desenvolvimento de dispositivos biomédicos que contenham uma parte geradora de RE e consigam melhorar a estabilidade e controle postural em pessoas com deficiência motora ou somato-sensorial. / Stochastic ressonance (SR) shows that certain levels of noise help to detect and transmit subliminal signals. Improvements in the performance of the somatosensory and motor systems (among others) have been obtained through the SR generated using additive signals with optimal intensity. The most commonly used additive signal (AS) is white Gaussian noise (WGN). This study aimed to verify whether it is possible to generate SR in the tactile sensory system using a sinusoidal signal as the AS and, at the same time, compare the results when the AS was WGN. The signals used in the experiments were defined as 3Hz for the stimulus signal (SS), to be recognized with the aid of ASs. These were either a sinuoid of 150Hz additive sinusoidal signal (ASS) or a white Gaussian noise additive signal (WGNAS) filtered at 150Hz. In the first part of the study a simulation of the Hodgkin and Huxley neuron model was made to verify if it could undergo SR for the same types of SS and AS mentioned before. A 3Hz sine signal was injected into the model with an intensity at which the neuron could not generate action potentials. When a higher frequency sine wave was added to this initial signal, the neuron could respond. The same behaviour was obtained when the additive signal used was WGN, giving, hence, a qualitative confirmation of our hypothesis. A psychophysical study was then carried out with 20 volunteers (11 men and 9 women) to verify the performance of the ASS and compare it with the WGNAS for the sensory detection of the sinusoidal SS. Initially, the detection threshold (DT) was found for each of the signals used. During the experiment, this value was used to determine the stimulus intensity. In the case of the SS the intensity was defined as 80 % of the DT of each volunteer. In the case of ASs, the intensity varied from 0% to 80% of the DT, in order to find the best proportion of AS added to detect the SS. In 90% of the cases it was possible to generate SR using either a fast frequency ASS or the WGNAS. Both ASs showed a statistically significant improvement in the detection rate (DR) of the SS. However, none of ASs performed better than the other, so that both types could be used to generate SR in the somatosensory system. This work has pioneered the use of a combination of sinusoids to generate SR and opens the door to the development of biomedical devices that help generate SR to provide stability improvement and better postural control for people with motor or somatosensory impairment.

Στην παρούσα διπλωματική εργασία μελετήθηκε και κατασκευάστηκε ένα σύστημα προσομοίωσης και εξομοίωσης των χαρακτηριστικών διαφόρων καναλιών επικοινωνίας ως προς την υποβάθμιση του σήματος και το θόρυβο που αυτά εισάγουν. Για τη διαδικασία σχεδίασης, υλοποίησης και ελέγχου του συστήματος, καθώς και για την εκτέλεση των πειραμάτων χρησιμοποιήθηκε η αναπτυξιακή πλατφόρμα ZedBoard. Στο πρώτο μέ- ρος της εργασίας παρουσιάζονται και αναλύονται τα μοντέλα των υποσυστημάτων που απαρτίζουν το κανάλι, καθώς και η υλοποίησή τους σε λογισμικό και υλικό. Οι δύο κύ- ριες μονάδες επεξεργασίας στο κανάλι είναι ένα FIR φίλτρο και μία γεννήτρια θορύβου. Το φίλτρο χρησιμοποιείται ως το στοιχείο που υποβαθμίζει το σήμα εισόδου, ενώ η γεννήτρια θορύβου εισάγει το τυχαίο σήμα στο κανάλι επικοινωνίας. Στο δεύτερο μέρος της εργασίας αναλύεται η αρχιτεκτονική του τελικού συστήματος, οι διεπαφές Ε/Ε που χρησιμοποιήθηκαν καθώς και η λογική ελέγχου που ακολουθήθηκε. Τέλος, περιγράφουμε την επικοινωνία και τη λογική ελέγχου του συστήματος, σε επίπεδο εντολών από το περιβάλλον της MATLAB. / The purpose of this thesis is to study and implement a simulation and emulation system of the characteristics of different communications channels concerning the degradation of the signal and the noise they introduce. For the process of design, implementation and monitoring of the system as well as to perform the experiment the ZedBoard development platform was used.In the first part we present and analyze the models of the subsystems which constitute the communication channel and also their implementation in software and hardware. The two main processing units in the channel is a FIR filter and a noise generator. The filter is used as the element that lowers the power of the input signal and the noise generator introduces the random signal to the communication channel.In the second part we analyze the architecture of the final system, the I / O interfaces used and the control logic followed.Finally, we describe the communication and control logic of the system. The commands used for this purpose are developed using the computing environment of MATLAB.

In this abstract, we present a novel primary-multiple separation scheme which makes use of the sparsity of both primaries and multiples in a transform domain, such as the curvelet transform, to provide estimates of each. The proposed algorithm utilizes seismic data as well as the output of a preliminary step that provides (possibly) erroneous predictions of the multiples. The algorithm separates the signal components, i.e., the primaries and multiples, by solving an optimization problem that assumes noisy input data and can be derived from a Bayesian perspective. More precisely, the optimization problem can be arrived at via an assumption of a weighted Laplacian distribution for the primary and multiple coefficients in the transform domain and of white Gaussian noise contaminating both the seismic data and the preliminary prediction of the multiples, which both serve as input to the algorithm.

No description available.

Feedforward is known to be one of the best methods for power amplifier linearization due to its superior linearization performance and broadband stable operation. However feedforward systems have relatively poor power efficiency and are complicated due to the presence of two nonlinear amplifiers and the requirements of amplitude, phase and delay matching within two different loops. In this thesis stochastic characterization of a simple feedforward system with autocorrelation analysis has been presented for Code Division Multiple Access (CDMA) applications taking the amplitude and delay mismatches into consideration. It has been assumed that, the input signal can be represented as Gaussian noise, main and error amplifiers can be modeled with third order AM/AM nonlinearities and there exists no phase mismatch within the loops. Hence closed form expressions, which relate the main channel and distorted adjacent channel power at any point in the feedforward circuitry to the system parameters, have been obtained. Consequently, a mathematical handy tool is achieved towards specifying the circuit parameters rapidly for optimum linearity performance and efficiency. The developed analytical model has been verified by Radio Frequency (RF) and system simulations. An alternative approach towards modeling feedforward systems for arbitrary signals has also been brought into consideration and has been verified with system simulations.

As an extension of the geometric Brownian motion, a geometric fractional Brownian motion (GFBM) is considered as a stock-price model. The modeled GFBM is compared with empirical Chinese stock prices. Comparisons are performed by considering logarithmic-return densities, autocovariance functions, spectral densities and trajectories. Since logarithmic-return densities of GFBM stock prices are Gaussian and empirical stock logarithmic-returns typically are far from Gaussian, a GFBM model may not be the most suitable stock price model.

This thesis is dedicated to the development of new energy detectors employed in the detection of unknown signals in the presence of non-Gaussian and non-independent noise samples. To this end, an extensive study has been conducted on di erent energy detection structures, and novel techniques have been proposed which are capable of dealing with these problematic situations. The energy detector is proposed as an optimum solution to detect uncorrelated Gaussian signals, or as a generalized likelihood ratio test to detect entirely unknown signals. In both cases, the background noise must be uncorrelated Gaussian. However, energy detectors degrade when the noise does not ful ll these characteristics. Therefore, two extensions are proposed. The rst is the extended energy detector, which deals with the problem of non-Gaussian noise; and the second is the preprocessed extended energy detector, used when the noise also possesses non-independent samples. A generalization of the matched subspace lter is likewise proposed based on a modi cation of the Rao test. In order to evaluate the expected improvement of these extensions with respect to the classical energy detector, a signalto- noise ratio enhancement factor is de ned and employed to illustrate the improvement achieved in detection. Furthermore, we demonstrate how the uncertainty introduced by the unknown signal duration can decrease the performance of the energy detector. In order to improve this behavior, a multiple energy detector, based on successive subdivisions of the original observation interval, is presented. This novel detection technique leads to a layered structure of energy detectors whose observation vectors are matched to di erent intervals of signal duration. The corresponding probabilities of false alarm and detection are derived for a particular subdivision strategy, and the required procedures for their general application to other possible cases are indicated. The experiments reveal the advantages derived from utilizing this novel structure, making it a worthwhile alternative to the single detector when a signi cant mismatch is present between the original observation length and the actual duration of the signal. / Moragues Escrivá, J. (2011). New energy detector extensions with application in sound based surveillance systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/11520 / Palancia

The Gaussian distribution is typically used to model the additive noise affecting communication systems. However, in many cases the noise cannot be modeled by a Gaussian distribution. In this thesis, we investigate the performance of different communication systems perturbed by non-Gaussian noise. Three families of noise are considered in this work, namely the generalized Gaussian noise, the Laplace noise/interference, and the impulsive noise that is modeled by an α-stable distribution. More specifically, in the first part of this thesis, the impact of an additive generalized Gaussian noise is studied by computing the average symbol error rate (SER) of one dimensional and two dimensional constellations in fading environment. We begin by the simple case of two symbols, i.e. binary phase shift keying (BPSK) constellation. From the results of this constellation, we extended the work to the average SER of an M pulse amplitude modulation (PAM). The first 2 − D constellation is the M quadrature amplitude modulation (QAM) (studied for two geometric shapes, namely square and rectangular), which is the combination of two orthogonal PAM signals (in-phase and quadrature phase PAM). In the second part, the system performance of a circular constellation, namely M phase shift keying (MPSK) is studied in conjunction with a Laplace noise with independent noise components. A closed form and an asymptotic expansion of the SER are derived for two detectors, maximum likelihood and minimum distance detectors. Next, we look at the intra cell interference of a full duplex cellular network which is shown to follow a Laplacian distribution with dependent, but uncorrelated, complex components. The densities of that interference are expressed in a closed form in order to obtain the SER of several communication systems (BPSK, PAM, QAM, and MPSK). Finally, we study the statistics of the α-stable distribution. Those statistics are expressed in closed form in terms of the Fox H function and used to get the SER of BPSK, PAM, and QAM constellations. An approximation and an asymptotic expansion for high signal to noise ratio are presented also and their efficiency is proved using Monte Carlo simulations. It is worth mentioning that all the error rates presented in this work are averaged over a generalized flat fading, namely the extended generalized K, which has the ability to capture most of the known fading distribution. Many special cases are treated and simpler closed form expressions of the probability of error are derived and compared to some previous reported results.

no / Abstract: We develop a novel approach to estimate the n unknown constituent frequencies of a sinusoidal signal that comprises of unknown number, n, of sinusoids of unknown phases and unknown amplitudes. The approach has been applied to multiple sinusoidal signals in the presence of white Gaussian noise with varying signal to noise ratio (SNR). The approach is based on eigenspace analysis of Hankel matrix formed with the samples from averaged frequency spectrum of the signal obtained through multiple measurements. The eigenspace analysis is based on the newly developed 3M relationship which reflects and exploits the relationship between the consecutive sets of Maximum, Middle and Minimum eigenvalues of square symmetric matrix of the Hankel matrix. The 3M relationship exhibits a pattern in line with the order of the Hankel matrix and leads to parametric estimation of the constituent sinusoids. This paper also presents the relationship equation between the size of 3M relationship pattern and the dimensions of the Hankel matrix. The performance of the developed approach has been tested to correctly estimate multiple constituent frequencies within a noisy signal.