Approximately 20 million people in the United States suffer from irreversible nerve damage and would benefit from a neuroprosthetic device modulated by a Brain-Computer Interface (BCI). These devices restore independence by replacing peripheral nervous system functions such as peripheral control. Although there are currently devices under investigation, contemporary methods fail to offer adaptability and proper signal recognition for output devices. Human anatomical differences prevent the use of a fixed model system from providing consistent classification performance among various subjects. Furthermore, notoriously noisy signals such as Electroencephalography (EEG) require complex measures for signal detection. Therefore, there remains a tremendous need to explore and improve new algorithms. This report investigates a signal-processing model that is better suited for BCI applications because it incorporates machine learning and fuzzy logic. Whereas traditional machine learning techniques utilize precise functions to map the input into the feature space, fuzzy-neuro system apply imprecise membership functions to account for uncertainty and can be updated via supervised learning. Thus, this method is better equipped to tolerate uncertainty and improve performance over time. Moreover, a variation of this algorithm used in this study has a higher convergence speed. The proposed two-stage signal-processing model consists of feature extraction and feature translation, with an emphasis on the latter. The feature extraction phase includes Blind Source Separation (BSS) and the Discrete Wavelet Transform (DWT), and the feature translation stage includes the Takagi-Sugeno-Kang Fuzzy-Neural Network (TSKFNN). Performance of the proposed model corresponds to an average classification accuracy of 79.4 % for 40 subjects, which is higher than the standard literature values, 75%, making this a superior model.

This thesis deals with copyright protection and content authentication for still images. New blind transform domain block based algorithms using one-level and two-level Discrete Wavelet Transform (DWT) were developed for copyright protection. The mobile number with international code is used as the watermarking data. The robust algorithms used the Low-Low frequency coefficients of the DWT to embed the watermarking information. The watermarking information is embedded in the green channel of the RGB colour image and Y channel of the YCbCr images. The watermarking information is scrambled by using a secret key to increase the security of the algorithms. Due to the small size of the watermarking information comparing to the host image size, the embedding process is repeated several times which resulted in increasing the robustness of the algorithms. Shuffling process is implemented during the multi embedding process in order to avoid spatial correlation between the host image and the watermarking information. The effects of using one-level and two-level of DWT on the robustness and image quality have been studied. The Peak Signal to Noise Ratio (PSNR), the Structural Similarity Index Measure (SSIM) and Normalized Correlation Coefficient (NCC) are used to evaluate the fidelity of the images. Several grey and still colour images are used to test the new robust algorithms. The new algorithms offered better results in the robustness against different attacks such as JPEG compression, scaling, salt and pepper noise, Gaussian noise, filters and other image processing compared to DCT based algorithms. The authenticity of the images were assessed by using a fragile watermarking algorithm by using hash function (MD5) as watermarking information embedded in the spatial domain. The new algorithm showed high sensitivity against any tampering on the watermarked images. The combined fragile and robust watermarking caused minimal distortion to the images. The combined scheme achieved both the copyright protection and content authentication.

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Structural Health Monitoring is a useful tool for reducing maintenance costs and improving the life and performance of engineering structures. Impedance-Based SHM utilizes the coupled electromechanical behavior of piezoelectric materials to detect adverse changes and material and mechanical failures of structures. Environmental variables such as temperature present a challenge to assessing the veracity of damage detected through statistical modeling of impedance signals. An effective frequency shift method was developed to compensate impedance measurements for changes resulting from environmental temperature fluctuations. This thesis investigates how the accuracy of this method can be improved and be applied to a 100oF range of temperatures. Building up the idea of eliminating temperature effects from impedance measurements, this thesis investigates the possibility of using statistical moments to create a temperature independent impedance baseline. / Master of Science

Cerebral autoregulation describes the clinically observed phenomenon that cerebral blood flow remains relatively constant in healthy human subjects despite large systemic changes in blood pressure, dissolved blood gas concentrations, heart rate and other systemic variables. Cerebral autoregulation is known to be impaired post ischaemic stroke, after severe head injury, in patients suffering from autonomic dysfunction and under the action of various drugs. Cerebral auto-regulation is a dynamic, multivariate phenomenon. Sensitive techniques are required to monitor cerebral auto-regulation in a clinical setting. This thesis presents 4 related signal processing studies of cerebral autoregulation. The first study shows how consideration of changes in blood gas concentrations simultaneously with changes in blood pressure can improve the accuracy of an existing frequency domain technique for monitoring cerebral autoregulation from spontaneous fluctuations in blood pressure and a transcranial doppler measure of cerebral blood flow velocity. The second study shows how the continuous wavelet transform can be used to investigate coupling between blood pressure and near infrared spectroscopy measures of cerebral haemodynamics in patients with autonomic failure. This introduces time information into the frequency based assessment, however neglects the contribution of blood gas concentrations. The third study shows how this limitation can be resolved by introducing a new time-varying multivariate system identification algorithm based around the dual tree undecimated wavelet transform. All frequency and time-frequency domain methods of monitoring cerebral autoregulation assume linear coupling between the variables under consideration. The fourth study therefore considers nonlinear techniques of monitoring cerebral autoregulation, and illustrates some of the difficulties inherent in this form of analysis. The general approach taken in this thesis is to formulate a simple system model; usually in the form of an ODE or a stochastic process. The form of the model is adapted to encapsulate a hypothesis about features of cerebral autoregulation, particularly those features that may be difficult to recover using existing methods of analysis. The performance of the proposed method of analysis is then evaluated under these conditions. After this testing, the techniques are then applied to data provided by the Laboratory of Human Cerebrovascular Physiology in Alberta, Canada, and the National Hospital for Neurology and Neurosurgery in London, UK.

Neste trabalho é desenvolvida uma metodologia baseada na aplicação do método dos momentos conjugado à aproximação por diferenças finitas, para análise no domínio do tempo da distribuição de correntes transitórias em meios condutores. O procedimento computacional permite que sejam considerados sistemas de condutores longos, com seção transversal genérica, discretizados em elementos filiformes. Assim, a equação integral que descreve o problema é substituída por uma representação matricial. No caso de meios não homogêneos, o método dos elementos finitos é usado para a obtenção da matriz que permite a solução do problema. Como o método proposto baseia-se na solução passo a passo no tempo, é interessante, para maior eficiência computacional, que as matrizes tenham sua dimensão reduzida, o que pode ser realizado por meio da Transformada Discreta Wavelet, como investigado no trabalho. Também é feita uma análise da estabilidade do procedimento computacional, para verificação das condições de aplicabilidade do mesmo. A validação do procedimento desenvolvido é feita a partir da comparação dos resultados obtidos para problemas com solução já conhecida por meio de medições ou por outros métodos de resolução. São apresentados resultados da aplicação do método proposto a alguns casos de interesse prático, na área de Compatibilidade Eletromagnética, destacando-se a análise do efeito de blindagem e o estudo de crosstalk em um sistema multicondutor. O procedimento desenvolvido ainda pode ser aprimorado com a utilização de elementos com formas mais gerais do que a filiforme proposta, permitindo sua extensão a problemas tridimensionais. Também pode ser estudado o pré-condicionamento da matriz a ser reduzida pela aplicação da Transformada Wavelet, a fim de permitir um melhor desempenho do processo computacional. / In this work, a methodology is developed, based on the application of the moment method associated to a finite difference approximation, for time domain analysis of transient current distribution in conducting media. The computational procedure allows that long conductors with any cross section can be considered, approximated by filamentary elements. Thus, the integral equation that describes the problem is substituted by a matrix representation. In the case of non homogeneous regions, the finite element method is used to obtain the matrix that allows the solution of the problem. As the proposed method works in a time step by step scheme, it is interesting, for increased computational efficiency, to reduce the size of the involved matrices. This can be done by application of the Discrete Wavelet Transform, as investigated in this work. An analysis of the numerical stability of the computational procedure is also done, aiming to establish its applicability conditions. Validation of the numerical procedure developed is done by comparing the results obtained for problems whose solution is known by measurement or by another method. Some problems of practical interest in Electromagnetic Compatibility were solved and the results are presented, concerning particularly shielding effects and multi conductor crosstalk. The developed procedure can be improved employing elements with more general shapes, besides the filamentary ones, allowing the consideration of three dimensional systems. Also, pre conditioning of the matrices before application of the Wavelet Transform can be studied, for a better performance of the method.

In recent years, response analysis of complex structures under impact loads has attracted a great deal of attention. For example, a collision or an accident that produces impact loads that exceed the design load can cause severe damage on the structural components. Although the AASHTO specification is used for impact-resistant bridge design, it has many limitations. The AASHTO specification does not incorporate complex and uncertain factors. Thus, a well-designed structure that can survive a collision under specific conditions in one region may be severely damaged if it were impacted by a different vessel, or if it were located elsewhere with different in-situ conditions. With these limitations in mind, we propose different solutions that use smart control technology to mitigate impact hazard on structures. However, it is challenging to develop an accurate mathematical model of the integrated structure-smart control systems. The reason is due to the complicated nonlinear behavior of the integrated nonlinear systems and uncertainties of high impact forces. In this context, novel algorithms are developed for identification, control and monitoring of nonlinear responses of smart structures under high impact forces. To evaluate the proposed approaches, a smart aluminum and two smart reinforced concrete beam structures were designed, manufactured, and tested in the High Impact Engineering Laboratory of Civil and Environmental Engineering at WPI. High-speed impact force and structural responses such as strain, deflection and acceleration were measured in the experimental tests. It has been demonstrated from the analytical and experimental study that: 1) the proposed system identification model predicts nonlinear behavior of smart structures under a variety of high impact forces, 2) the developed structural health monitoring algorithm is effective in identifying damage in time-varying nonlinear dynamic systems under ambient excitations, and 3) the proposed controller is effective in mitigating high impact responses of the smart structures.

O fresamento do aço inoxidável austenítico é um processo importante para a produção de peças em que se deseja alta resistência mecânica e à corrosão. No entanto, a usinagem desse material representa um desafio por suas características adversas ao corte. A alta taxa de encruamento e a alta dureza relativa fazem-no resistente ao corte, podendo gerar vibrações em diferentes faixas de frequência. Uma técnica importante ao processamento de sinais de vibração é a Transformada de Wavelet que permite analisar diferentes frequências do sinal através da subdivisão em aproximações e detalhamentos. Neste trabalho analisaram-se vibrações em alta e baixa frequência geradas no fresamento frontal do aço inoxidável austenítico AISI 316 a partir de sinais de força, coletados por meio de um dinamômetro piezelétrico e processados via Transformada de Wavelet Discreta. Também se fez a investigação dos perfis de rugosidade, dos parâmetros de rugosidade média (Ra) e média parcial (Rz) e das ondulações gerados na superfície fresada. Nos ensaios, foram utilizados insertos com três raios de ponta distintos, hastes da fresa com três diferentes comprimentos em balanço e foram variadas a rotação do eixo-árvore e a profundidade de corte axial em três níveis cada, totalizando 81 combinações de parâmetros. Constatou-se que a profundidade de corte representou a maior influência na vibração. Na usinagem com rotações abaixo do valor mínimo recomendado pelo fabricante (1600 rpm), houve dificuldades na formação e remoção do cavaco. A modificação do raio de ponta influenciou mais a vibração em pequenas profundidades de corte ou em zonas próximas às condições de instabilidade. O comprimento da haste mostrou comportamentos diferentes para a vibração, podendo estar relacionado com a mudança das frequências naturais do sistema e também pode definir entrada em regime instável. Verificou-se correlação do detalhamento (D1) da força resultante (vibração em altas frequências) com o parâmetro Ra para condições de vibrações intensas (maiores amplitudes), mas em regime estável. Assim, o parâmetro D1 pode ser utilizado na detecção de vibrações chatter no processo de fresamento frontal do aço inoxidável AISI 316. / The milling of austenitic stainless steel is important process for the production of part that require mechanical and corrosion resistance. However, the machining of this steel represents a challenge by its adverse features. The high hardening rate and the high relative hardness make it resistant to cutting and can generate vibrations in different frequency ranges. An important technique for the processing of vibration signals is the Wavelet Transform that allows the analysis of different signal frequencies through the subdivisions into approximations and details. In this work, high and low frequency vibration generated in end milling of AISI 316 stainless steel were analyzed from force signals collected through a piezoelectric dynamometer and processed via Wavelet Discrete Transform. Besides, the roughness profiles were investigated, as well as average (Ra) and partial mean (Rz) roughness parameters, and waviness generated on the milled surface. Three different insert nose radius, end mill tool lengths, depths of cut and spindle speeds were used in the experiments, totaling 81 combinations of parameters. It was found that depth of cut represented the greatest influence on vibration. In end milling with spindle speed below the minimum recommended by the tool manufacturer (1600 rpm) it occurred difficulties in the chip formation and removal. The modification of tool nose radius greater influenced the vibration at small depths of cut or in regions close to the stability limit. The end mill tool length showed different behaviors for the vibration, which may be related to the change of natural frequencies of the mechanical system and may also define an unstable state. The correlation of detail (D1) of the resulting force (vibration at high frequencies) with the parameter Ra for intense vibration conditions (larger amplitudes) was verified, but in stable state. Thus, D1 can be used for detecting chatter in end milling process of AISI 316 stainless steel.

Este trabalho apresenta um estudo comparativo entre diferentes famílias de transformada Wavelet aplicadas à análise cepstral de sinais digitais de fala humana, com o objetivo específico de determinar o período de pitch dos mesmos e, ao final, propõe um algoritmo diferencial para realizar tal operação, levando-se em consideração aspectos importantes do ponto de vista computacional, tais como: desempenho, complexidade do algoritmo, plataforma utilizada, dentre outros. São apresentados também, os resultados obtidos através da implementação da nova técnica (baseada na transformada wavelet) em comparação com a abordagem tradicional (baseada na transformada de Fourier). A implementação da técnica foi testada em linguagem C++ padrão ANSI sob as plataformas Windows XP Professional SP3, Windows Vista Business SP1, Mac OSX Leopard e Linux Mandriva 10. / This work presents a comparative study between different family of wavelets applied on cepstral analysis of the digital speech human signal with specific objective for determining of pitch period of the same and in the end, proposes an differential algorithm to make such a difference operation take into consideration important aspects of computational point of view, such as: performance, algorithm complexity, used platform, among others. They are also present, the results obtained through of the technique implementation compared with the traditional approach. The technique implementation was tested in C++ language standard ANSI under the platform Windows XP Professional SP3 Edition, Windows Vista Business SP1, MacOSX Leopard and Linux Mandriva 10.