Auditory brainstem response (ABR) evaluation has been one of the most reliable methods for evaluating hearing loss. Clinically available methods for ABR tests require averaging for a large number of sweeps (~1000-2000) in order to obtain a meaningful ABR signal, which is time consuming.  This study proposes a faster new method for ABR filtering based on wavelet-Kalman filter that is able to produce a meaningful ABR signal with less than 500 sweeps. The method is validated against ABR data acquired from 7 normal hearing subjects with different stimulus intensity levels, the lowest being 30 dB NHL. The proposed method was able to filter and produce a readable ABR signal using 400 sweeps; other ABR signal criteria were also presented to validate the performance of the proposed method.

Magnetic Resonance Imaging (MRI) is a common medical imaging tool that have beenused in clinical industry for diagnostic and research purposes. These images are subjectto noises while capturing the data that can eect the image quality and diagnostics.Therefore, improving the quality of the generated images from both resolution andsignal to noise ratio (SNR) perspective is critical. Wavelet based denoising technique isone of the common tools to remove the noise in the MRI images. The noise is eliminatedfrom the detailed coecients of the signal in the wavelet domain. This can be done byapplying thresholding methods. The main task here is to nd an optimal threshold andkeep all the coecients larger than this threshold as the noiseless ones. Noise InvalidationDenoising technique is a method in which the optimal threshold is found by comparingthe noisy signal to a noise signature (function of noise statistics). The original NIDeapproach is developed for one dimensional signals with additive Gaussian noise. In thiswork, the existing NIDe approach has been generalized for applications in MRI imageswith dierent noise distribution. The developed algorithm was tested on simulated datafrom the Brainweb database and compared with the well-known Non Local Mean lteringmethod for MRI. The results indicated better detailed structural preserving forthe NIDe approach on the magnitude data while the signal to noise ratio is compatible.The algorithm shows an important advantageous which is less computational complexitythan the NLM method. On the other hand, the Unbiased NLM technique is combinedwith the proposed technique, it can yield the same structural similarity while the signalto noise ratio is improved.

The safety of pipelines distributed in the infrastructure of many industries has become very important since the industrial revolution. The guided ultrasonic wave technique can provide the possibility for rapid screening in long pipelines with corrosion. Especially the torsional mode T(0,1) of guided waves has been used in the cases of the pipe in the hidden region substantially. The ability of evaluating the inaccessible areas of the pipe makes the guided ultrasonic wave technique sit high on the roster of non-destructive testing tool for pipe inspection. However, the problem arises when attempting to detect the corrosions at the welded support bracket or under the bitumen coating on the pipe. The signal reflected from the corrosion will be covered by a large signal induced by the welded support or attenuated by the bitumen coating seriously. Therefore, the effects of welded support and bitumen coating on the T(0,1) mode are investigated by the experimental and the simulative methods. The continuous wavelet transform analysis is the signal processing method to extract the hidden signal of corrosion in this dissertation. There are five test pipes in the experiments. The response of the normal welded support is studied on the #1 test pipe. The #2 test pipe is used for attenuation investigation. The reflected signals of the features on the #3, #4, and #5 test pipes are measured and processed by continuous wavelet transform during defect detection process. In addition, the linear hexahedron elements are used to build the finite element models of the 6-inch steel pipe with support bracket and the pipe with bitumen coating. It is found that the effects of support bracket on the reflection comprise mode conversion, delayed appearance, trailing echoes, and frequency dependent behavior. When the T(0,1) mode impinges on to the support bracket, it will convert into the A0 mode inside the support due to the circumferential disturbance on the pipe surface. The reflection of the support bracket is identified as three parts formed by the direct echo, delayed echo and the trailing echo. The constructive interference of the A0 mode reflecting from the boundaries inside the support causes that the reflection spectrum shows two maxima peak at around 20-22 kHz (frequency regime of 0.0) and 32-34 kHz (frequency regime of 4.0) from both the experimental and simulated results. For the bitumen coating, the data collected from the welds and defects under the bitumen coating on the #2 test pipe show the attenuation effect on guided wave propagation and the difficulty of minor corrosion detection. In the finite element model of coated pipe, the results of predicted attenuation curves of T(0,1) mode indicate that the attenuation effect on guided wave propagation is aggravated with the increased value of the thickness, density or damping factor of the coated layer. Especially, in the case of 5-mm, the predicted attenuation curve shows a maximum point. Before this point, the attenuation increases with the operating frequency. For long range pipe inspection, it is the best way to avoid choosing the operating frequency around the corresponding frequency of the point. The measured data of corrosion affected by the welded support or the coated bitumen layer was processed by continuous wavelet transform to form a time-frequency analysis. The corrosion signals were identified in the contour map of the wavelet coefficient successfully. The understanding of the guided wave propagation on the pipe welded with support or pipe coated with bitumen is helpful to interpret the reflected signals. The use of continuous wavelet transform on signal processing techniques can improve the ability of defect detection on pipe with complex geometries.

Many hydrocarbon detection techniques have been developed for decades and one of the most efficient techniques for hydrocarbon exploration in recent years is well known as amplitude versus offset analysis (AVO). However, AVO analysis does not always result in successful hydrocarbon finds because abnormal seismic amplitude variations can sometimes be caused by other factors, such as alternative lithology and residual hydrocarbons in certain depositional environments. Furthermore, not all gas fields are associated with obvious AVO anomalies. Therefore, new techniques should be applied to combine with AVO for hydrocarbon detection. In my thesis, I, through case studies, intend to investigate and validate the wave decomposition technique as a new tool for hydrocarbon detection which decomposes seismic wave into different frequency contents and may help identify better the amplitude anomalies associated with hydrocarbon occurrence for each frequency due to seismic attenuation. The wavelet decomposition analysis technique has been applied in two geological settings in my study: clastic reservoir and carbonate reservoir. Results from both cases indicate that the wavelet decomposition analysis technique can be used for hydrocarbon detection effectively if the seismic data quality is good. This technique can be directly applied to the processed 2D and 3D pre-stack/post-stack data sets (1) to detect hydrocarbon zones in both clastic and carbonate reservoirs by analyzing the low frequency signals in the decomposed domain and (2) to identify thin beds by analyzing the high frequency signals in the decomposed domain. In favorable cases, the method may possibly help separate oil from water in high-porosity and high-permeability carbonate reservoirs deeply buried underground. Therefore, the wavelet analysis would be a powerful tool to assist geological interpretation and to reduce risk for hydrocarbon exploration.

The Ultra-Wideband (UWB) communication technology has been extensively attended in recent years. In this thesis, we propose the improved selective-Rake receiver and analyze the performance on UWB channels. The UWB transmission channels are modeled with statistical methods and its fading characteristics are discussed. Different impulse radio properties for the UWB communication system are analyzed. The system performance and design complexity issues of selective-Rake receiver (SRake) are studied. Rake receiver has difficulties achieving desired system performance in the dense multipath environment. The main ideas of SRake receiver are to obtain the SNR level on known multipath channel and to determine the desired number of Rake fingers. Matched filters and maximum likelihood detectors are utilized in the implementation of the SRake to estimate the signal time delay. The CLEAN algorithm is then used in selecting the paths with relatively high energy. Furthermore, we also propose a noise cancellation scheme for performance improvement in the SRake receiver. In the noise cancellation scheme, the multiresolution property of wavelet transform is used for filtering the noise interference caused by the rapid fluctuation factor. In addition, a two-stage search is combined with the original CLEAN algorithm to increase the accuracy of path selection. From our simulation results on the UWB channels, the improved SRake receiver, with noise cancellation and two-stage search, indeed has high SRake output SNR and better path accuracy than the original SRake receiver.

The purpose of this research is the estimation for the trend of diastolic pressure of surgical patients utilizing non-invasive photo-plethysmography (PPG) signal. There are two major ways to measure blood pressure during medical treatment : invasive and non-invasive methods. Both them have advantages and disadvantages. For invasive method, it is used for surgical operations. Although it can response the true situation of arterial blood pressure, the damage and uncomfortable are the most disadvantages for itself. And for non-invasive method, it is convenient to use but the measurement results have lower accuracy. In this research, we try to estimate the continuous trend of diastolic pressure utilizing PPG signal. And calculate the accuracy of the results.

As the digital technology advances with each passing day and the internet is evolving so quickly, the use of digital images is increasing on the demand. More information is showed in terms of digital patterns or images in our daily life. Besides retrieving image data from a given image database by context, we can alternatively do that by the image features we prescribed. This method is then called content-based image retrieval, CBIR. The wavelet transform possesses the power of multi-resolutional analysis for digital images. It¡¦s bands are mutually independent so that good results can often be obtained from partial analyses. Although wavelet transform is usually used for image compression and texture analysis, it has also many recent applications in the area of image retrieval. In this research, we propose the use of some new image roughness features to represent the variation of image textures. After an image is transformed on the wavelet, we collect the roughness features as well as wavelet energy features from each band. These features are then used to sort out desired images. We can show that the features as used in this work can be extracted even when the images are altered by some rotation, partial magnification or viewpoint changes.

The main advantage of wavelet transform relative to its Fourier analysis counterpart is its suitability to deal with transient signals. Furthermore, wavelet packet transform has very good frequency analytic ability with the result that it is developing in very fast speed and widespread researched and used in industry and academia. We study the characteristics of fiber optic sensors by applying wavelet transform. Hence, in this paper, the traditional Fourier analysis is taken as a basis, and the wavelet packet analysis is taken as a comparison. The major objects include: (1) calibration of hydrophones; (2) vibration measurement. In calibration of hydrophones, the experimental results show a 2.72 dB re V/£gPa inaccuracies and a 5.3 dB re V/£gPa standard deviation by Fourier analysis, but 0.5 dB inaccuracies and 1.6 dB re V/£gPa standard deviation by wavelet packet analysis. It shows that the wavelet packet analysis has better analytic ability than that of traditional Fourier analysis. In vibration measurement, we utilize FBG interferometers to measure stable vibration. The experimental results denote that wavelet packet analysis has excellent frequency analytic ability as Fourier analysis. Besides, in obtaining transient characteristic signals induced by falling stones, the results appear that wavelet packet analysis has better resolution and identification capability relative to Fourier analysis.

In this thesis, a three-word and four-word Mandarin phrases speech recognition system is developed. This system contains two recordings of twenty-four thousand three-word phrases and twenty-two thousand four-word phrases in the database. And it applies MFCC, mono-syllable HMM¡¦s and speech-text alignment scheme to select the initial phrase candidates. A wavelet transform based vowel segmentation technique and a Mandarin pitch identification method is then followed to increase the phrase correct identification rate and obtain the final answer. Experimental results indicate that 92% and 96% correct rates can be achieved for three-word and four-word phrases recognition problems respectively, under the conditions that the first recording of this database is used for training and the second one is for testing. For the speaker-dependent case, the correct phrase can be found within 1 second, using a PC with Intel Celeron 2.4 GHz CPU and RedHat Linux 9.0 Operation System.

The possibility and feasibility of experimental detection of localized defects in tubes using laser-induced ultrasonic wave approach through Thermo Acousto Photonic Non Destructive Evaluation (TAP-NDE) and Signal processing through wavelet transform is examined in this research. Guided waves in cylindrical surfaces provide solutions for detection of different defects in the material. Several experiments were conducted to this respect. Wave propagation in both axial and circumferential directions was studied. The dispersive wave propagation of ultrasonic waves in hollow cylinders has been investigated experimentally, primarily for use in non-contact and nondestructive inspections of pipes and tubes. The laser ultrasonic waves propagated in cylindrical waveguides are particularly attractive because of their unique characteristics in the applications of nondestructive evaluation (NDE). Contrary to studies making use of only axially symmetric guided waves in hollow cylinders, here are analyzed also nonaxisymmetric waves. The analysis of data is made by using the Gabor wavelet transform. The capability of modeling the guided wave dispersion in hollow cylinders is used in developing guided wave experimental techniques for flaw detection. Good agreement was obtained when comparing the dispersion spectra between theory and experimentation. Measurement of group velocities of guided waves, which are obtained directly from the wavelet transform coefficients, can be used to determine allocation and sizing of flaws.