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No / Word spotting in continuous speech is considered a challenging issue due to dynamic nature of speech. Literature contains a variety of novel techniques for the isolated word recognition and spotting. Most of these techniques are based on pattern recognition and similarity measures. This paper amalgamates the use of different techniques that includes wavelet transform, feature extraction and Euclidean distance. Based on the acoustic features, the proposed system is capable of identifying and localizing a target (test) word in a continuous speech of any length. Wavelet transform is used for the time-frequency representation and filtration of speech signal. Only high intensity frequency components are passed to feature extraction and matching process resulting robust performance in terms of matching as well as computational cost.

In this dissertation we focus on fractional-order dynamical systems and classify these problems as optimal control of system described by fractional derivative, fractional-order nonlinear differential equations, optimal control of systems described by variable-order differential equations and delay fractional optimal control problems. These problems are solved by using the spectral method and reducing the problem to a system of algebraic equations. In fact for the optimal control problems described by fractional and variable-order equations, the variables are approximated by chosen wavelets with unknown coefficients in the constraint equations, performance index and conditions. Thus, a fractional optimal control problem is converted to an optimization problem, which can be solved numerically. We have applied the new generalized wavelets to approximate the fractional-order nonlinear differential equations such as Riccati and Bagley-Torvik equations. Then, the solution of this kind of problem is found using the collocation method. For solving the fractional optimal control described by fractional delay system, a new set of hybrid functions have been constructed. Also, a general and exact formulation for the fractional-order integral operator of these functions has been achieved. Then we utilized it to solve delay fractional optimal control problems directly. The convergence of the present method is discussed. For all cases, some numerical examples are presented and compared with the existing results, which show the efficiency and accuracy of the present method.

La visión involucra diferentes mecanismos fisiológicos y cerebrales. Abarca el sistema oculomotor, que se encarga de mover los ojos para situarlos sobre lo que se quiere observar, las células fotorreceptoras que convierten los estímulos lumínicos en señales eléctricas, y el lóbulo occipital encargado de interpretar dichas señales y formar la imagen en el cerebro. Demanda, además, que entren en juego funciones cognitivas del cerebro como la memoria semántica, la memoria a largo plazo y la memoria de trabajo. La lectura es una actividad cotidiana en la que resultan más evidentes y fáciles de manipular estos procesos. Por lo tanto, entender cómo leemos permite comprender, en parte, cómo funcionan estas áreas, y una manera de lograr dicha comprensión es mediante el análisis de la información provista por los movimientos oculares durante la lectura. Una técnica no invasiva para detectar dicho movimientos para su análisis posterior es la utilización del eye-tracker. Tanto en la observación libre como durante la lectura, los ojos realizan fijaciones y sacadas entre las fijaciones, y durante éstas se producen pequeños movimientos balísticos llamados microsacádicos. En diferentes trabajos se muestra que estos movimientos están asociados a procesos cognitivos y a la tarea de mantener la imagen en la retina, aunque no hay un criterio unificado sobre cómo detectarlos. Por otro lado, el envejecimiento suele traer consigo un deterioro del tejido cerebral, en ocasiones normal y en otras patológico, que repercute principalmente en las áreas cerebrales asociadas a la memoria y a diferentes procesos cognitivos. En esta tesis analizamos los movimientos microsacádicos presentes en las fijaciones registradas con un eye-tracker durante lecturas realizadas por grupos de adultos jóvenes, de adultos mayores sanos y de adultos mayores con deterioro cognitivo incipiente. Presentamos un método diferente de detección de los movimientos microsacádicos, combinando la Transformada Wavelet Continua que explota su naturaleza balística, junto con la localización de outliers en el espacio de velocidades. Una vez extraídos los movimientos microsacádicos mostramos, utilizando Modelos Lineales Mixtos, de qué manera estos movimientos se ven afectados por diferentes estímulos para cada uno de los grupos de sujetos. Los estímulos considerados son los tipos de oraciones y la predictibilidad, frecuencia y largo de las palabras. También examinamos la función que cumplen los microsacádicos durante la lectura mediante el análisis de la orientación que éstos presentan en los distintos tipos de fijaciones. Para ello, clasificamos previamente las fijaciones sobre la lectura, y realizamos histogramas angulares para los distintos tipos de fijaciones y para cada uno de los diferentes grupos de sujetos. / Vision involves different physiological and cerebral mechanisms. It involves the ocu- lomotor system, which is responsible for moving the eyes to place them on what the observer wants to observe, the photoreceptor cells that convert light stimuli into electrical signals, and the occipital lobe responsible for interpreting these signals and forming the image in the brain. It also requires the cognitive functions of the brain such as semantic memory, long-term memory and working memory to come into play. Reading is a daily activity in which these processes are most evident and easier to manipulate. Therefore, understanding how we read, partially allows us to understand how these areas works, and one way to achieve this understanding is by analyzing the information provided by eye movements during reading. A non-invasive technique to detect such movements for later analysis is the use of the eye-tracker. Both in free observation and during reading, the eyes perform fixations and saccades between the fixations and, during these ones, occur small ballistic movements called microsaccadic movements. Different works show that these movements are associated with cognitive processes and with the task of maintaining the image on the retina, although there is no unified criterion on how to detect them. On the other hand, aging usually brings with it a deterioration of brain tissue, someti- mes normal and sometimes pathological, which mainly affects the brain areas associated with memory and different cognitive processes. In this thesis we analyze the microsaccadic movements present in the fixations recorded with an eye-tracker during reading, performed by groups of young adults, healthy older adults and elder adults with early cognitive impairment. We present a different method for detecting microsaccadic movements, combining the Continuous Wavelet Transform that exploits their ballistic nature, together with the localization of outliers in velocity space. Once the microsaccadic movements are extracted we show, using Linear Mixed Models, how they are affected by different stimuli for each one of the groups of subjects. The considered stimuli are the types of sentences and the predictability, frequency and length of words. We also examined the role of microsaccades during reading by analyzing their orientation during different types of fixations. For this purpose, we previously classified the fixations during reading, and we made angular histograms for the different kind of fixations and for each one of the different groups of subjects

No / In this work, we discuss two new multicarrier modulating kernels that can be adopted for multicarrier signaling. These multicarrier transforms are the fractional Forurier transform (FrFT) and discrete wavelet transforms (DWT). At first, we relate the transforms in terms of mathematical relationships, and then using numerical and simulation comparisons we show their performances in terms of bit error ratio (BER) for Multiple Input Multiple Output (MIMO) applications. Numerical results using BPSK and QPSK support that both can be applied for multicarrier signaling, however, it can be resource effective to drive the DWT as the baseband multicarrier kernel at the expense of the FrFT

Saturn's rings are a complex, dynamic system that can provide unique insight into the structure and features of the planet and surrounding system. We use stellar occultation data of Saturn's rings collected from the Cassini Ultraviolet Imaging Spectrograph to visualize and analyze bending waves present within the rings. Analysis of the propagation of these waves gives insight into the surface mass density of the local ring region and can be used to further our understanding of ring dynamics and ring formation. Our analysis of the Mimas 7:4 bending wave estimated a surface mass density between 30 g cm-2 and 43 g cm-2, corroborating the findings of Spilker et al. (2004) of 47 ± 6.2 g cm-2 and supporting our current understanding of linear wave theory. Our analysis of the Mimas 4:2 bending wave estimated the surface mass density to be between 33 g cm-2 and 47 g cm-2 and was of particular interest since this wave is found in the relatively uncharacterized B ring region.

The aim of this thesis is to design a system for automated accident detection in intersections. The input to the system is a three-second audio signal. The system can be operated in two modes: two-class and multi-class. The output of the two-class system is a label of ?crash? or ?non-crash?. In the multi-class system, the output is the label of ?crash? or various non-crash incidents including ?pile drive?, ?brake?, and ?normal-traffic? sounds. The system designed has three main steps in processing the input audio signal. They are: feature extraction, feature optimization and classification. Five different methods of feature extraction are investigated and compared; they are based on the discrete wavelet transform, fast Fourier transform, discrete cosine transform, real cepstrum transform and Mel frequency cepstral transform. Linear discriminant analysis (LDA) is used to optimize the features obtained in the feature extraction stage by linearly combining the features using different weights. Three types of statistical classifiers are investigated and compared: the nearest neighbor, nearest mean, and maximum likelihood methods. Data collected from Jackson, MS and Starkville, MS and the crash signals obtained from Texas Transportation Institute crash test facility are used to train and test the designed system. The results showed that the wavelet based feature extraction method with LDA and maximum likelihood classifier is the optimum design. This wavelet-based system is computationally inexpensive compared to other methods. The system produced classification accuracies of 95% to 100% when the input signal has a signal-to-noise-ratio of at least 0 decibels. These results show that the system is capable of effectively classifying ?crash? or ?non-crash? on a given input audio signal.

Spaceborne sensors, which collect imagery of the Earth in various spectral bands, are limited by the data transmission rates. As a result the multispectral bands are transmitted at a lower resolution and only the panchromatic band is transmitted at its full resolution. The information contained in the multispectral bands is an invaluable tool for land use mapping, urban feature extraction, etc. However, the limited spatial resolution reduces the appeal and value of this information. Pan sharpening techniques enhance the spatial resolution of the multispectral imagery by extracting the high spatial resolution of the panchromatic band and adding it to the multispectral images. There are many different pan sharpening methods available like the ones based on the Intensity-Hue-Saturation and the Principal Components Analysis transformation. But these methods cause heavy spectral distortion of the multispectral images. This is a drawback if the pan sharpened images are to be used for classification based applications. In recent years, multiresolution based techniques have received a lot of attention since they preserve the spectral fidelity in the pan sharpened images. Many variations of the multiresolution based techniques exist. They differ based on the transform used to extract the high spatial resolution information from the images and the rules used to synthesize the pan sharpened image. The superiority of many of the techniques has been demonstrated by comparing them with fairly simple techniques like the Intensity-Hue-Saturation or the Principal Components Analysis. Therefore there is much uncertainty in the pan sharpening community as to which technique is the best at preserving the spectral fidelity. This research investigates these variations in order to find an answer to this question. An important parameter of the multiresolution based methods is the number of decomposition levels to be applied. It is found that the number of decomposition levels affects both the spatial and spectral quality of the pan sharpened images. The minimum number of decomposition levels required to fuse the multispectral and panchromatic images was determined in this study for image pairs with different resolution ratios and recommendations are made accordingly.

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