We address the problem of image denoising for additive white Gaussian noise (AWGN), Poisson noise, and Chi-squared noise scenarios. Thermal noise in electronic circuitry in camera hardware can be modeled as AWGN. Poisson noise is used to model the randomness associated with photon counting during image acquisition. Chi-squared noise statistics are appropriate in imaging modalities such as Magnetic Resonance Imaging (MRI). AWGN is additive, while Poisson noise is neither additive nor multiplicative. Although Chi-squared noise is derived from AWGN statistics, it is non-additive. Mean-square error (MSE) is the most widely used metric to quantify denoising performance. In parametric denoising approaches, the optimal parameters of the denoising function are chosen by employing a minimum mean-square-error (MMSE) criterion. However, the dependence of MSE on the noise-free signal makes MSE computation infeasible in practical scenarios. We circumvent the problem by adopting an MSE estimation approach. The ground-truth-independent estimates of MSE are Stein’s unbiased risk estimate (SURE), Poisson unbiased risk estimate (PURE) and Chi-square unbiased risk estimate (CURE) for AWGN, Poison and Chi-square noise models, respectively. The denoising function is optimized to achieve maximum noise suppression by minimizing the MSE estimates. We have chosen the bilateral filter as the denoising function. Bilateral filter is a nonlinear edge-preserving smoother. The performance of the bilateral filter is governed by the choice of its parameters, which can be optimized to minimize the MSE or its estimate. However, in practical scenarios, MSE cannot be computed due to inaccessibility of the noise-free image. We derive SURE, PURE, and CURE in the context of bilateral filtering and compute the parameters of the bilateral filter that yield the minimum cost (SURE/PURE/CURE). On processing the noisy input with bilateral filter whose optimal parameters are chosen by minimizing MSE estimates (SURE/PURE/CURE), we obtain the estimate closest to the ground truth. We denote the bilateral filter with optimal parameters as SURE-optimal bilateral filter (SOBF), PURE-optimal bilateral filter (POBF) and CURE-optimal bilateral filter (COBF) for AWGN, Poisson and Chi-Squared noise scenarios, respectively. In addition to the globally optimal bilateral filters (SOBF and POBF), we propose spatially adaptive bilateral filter variants, namely, SURE-optimal patch-based bilateral filter (SPBF) and PURE-optimal patch-based bilateral filter (PPBF). SPBF and PPBF yield significant improvements in performance and preserve edges better when compared with their globally-optimal counterparts, SOBF and POBF, respectively. We also propose the SURE-optimal multiresolution bilateral filter (SMBF) where we couple SOBF with wavelet thresholding. For Poisson noise suppression, we propose PURE-optimal multiresolution bilateral filter (PMBF), which is the Poisson counterpart of SMBF. We com-pare the performance of SMBF and PMBF with the state-of-the-art denoising algorithms for AWGN and Poisson noise, respectively. The proposed multiresolution-based bilateral filtering techniques yield denoising performance that is competent with that of the state-of-the-art techniques.

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.

Millions of people across the world currently have noise induced hearing loss, and many are working in conditions with both continuous Gaussian and non-Gaussian noises that could affect their hearing. It was hypothesized that the energy of the noise was the cause of the hearing loss and did not depend on temporal pattern of a noise. This was referred to as the equal energy hypothesis. This hypothesis has been shown to have limitations though. This means that there is a difference in the types of noise a person receives to induce hearing loss and it is necessary to build a system that can easily mimic various conditions to conduct research. This study builds a system that can produce both non-Gaussian impulse/impact noises and continuous Gaussian noise. It was found that the peak sound pressure level of the system could reach well above the needed 120 dB level to represent acoustic trauma and could replicate well above the 85 dB A-weighted sound pressure level to produce conditions of gradual developing hearing loss. The system reached a maximum of 150 dB sound peak pressure level and a maximum of 133 dB A-weighted sound pressure level. Various parameters could easily be adjusted to control the sound, such as the high and low cutoff frequency to center the sound at 4 kHz. The system build can easily be adjusted to create numerous sound conditions and will hopefully be modified and improved in hopes of eventually being used for animal studies to lead to the creation of a method to treat or prevent noise induced hearing loss.

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