Several adaptive filters were investigated to enhance speech auditory brainstem responses (speech ABR). The objective was to shorten the long recording time currently needed by the standard coherent averaging method to obtain acceptable performance, which has limited the clinical adoption of speech ABR. Five algorithms were implemented: Wiener Filter (WF), Steepest Descent (SD), Adaptive Noise Cancellation (ANC) based on Least-Mean-Square error (LMS) and normalized LMS error (nLMS), and a multi-adaptive cascade combination of SD and LMS. The performance of the adaptive filters was assessed on speech ABR data gathered from several subjects and compared with coherent averaging using the overall Signal-to-Noise Ratio (SNR), the local SNR around the fundamental frequency and the first formant, and Mean-Square-Error (MSE) in the time and frequency domains. The adaptive filters could reduce the time needed, by at least one order of magnitude, for obtaining comparable signal quality as that obtained with coherent averaging.

A consensus on how to characterise the anterograde and retrograde memory processes that are lost or spared after hippocampal damage has not been reached. In this thesis, I critically re-examine the empirical literature and the assumptions behind current theories. I formulate a coherent view of what makes a task hippocampally dependent at acquisition and how this relates to its long-term fate. Findings from a neural net simulation indicate the plausibility of my proposals. My proposals both extend and constrain current views on the role of the hippocampus in the rapid acquisition of information and in learning complex associations. In general, tasks are most likely to require the hippocampus for acquisition if they involve rapid, associative learning about unfamiliar, complex, low salience stimuli. However, none of these factors alone is sufficient to obligatorily implicate the hippocampus in acquisition. With the exception of associations with supra-modal information that are always dependent on the hippocampus, it is the combination of factors that is important. Detailed, complex information that is obligatorily hippocampally-dependent at acquisition remains so for its lifetime. However, all memories are semanticised as they age through the loss of detailed context-specific information and because generic cortically-represented information starts to dominate recall. Initially hippocampally dependent memories may appear to become independent of the hippocampus over time, but recall changes qualitatively. Multi-stage, lifelong post-acquisition memory processes produce semanticised re-representations of memories of differing specificity and complexity, that can serve different purposes. The model simulates hippocampal and cortical interactions in the acquisition and maintenance of episodic and semantic events, and behaves in accordance with my proposals. In particular, conceptualising episodic and semantic memory as representing points on a continuum of memory types appears viable. Support is also found for proposals on the relative importance of the hippocampus and cortex in the rapid acquisition of information and the acquisition of complex multi-model information; and the effect of existing knowledge on new learning. Furthermore, episodic and semantic events become differentially dependent on cortical and hippocampal components. Finally, as a memory ages, it is automatically semanticised and becomes cortically dependent.

The Pyramid Sensor (PS) is a promising wavefront sensor (WFS) for astronomical adaptive optics (AO) due to its potential to increase the number of accessible scientific targets by more efficiently using guide star (GS) photons. This so-called magnitude gain, as well as the key role played by the PS in several novel multi-reference wavefront sensing schemes have generated intense interest in the device. The diffraction based theory of PS and the underlying optical shop test, the Foucault knife-edge test, is reviewed. The theory is applied to calculate the magnitude gain. The impact of the magnitude gain on the number of galaxies accessible to observation with classical A0 on a TMT sized telescope for the Virgo Cluster Catalogue is assessed via simulations. Additional simulation results are shown to elucidate the impact of various parameters of the pyramidal prism on the magnitude gain. The results of experiments conducted in the UVIC A0 lab with a prototype Id PS are discussed. The Id PS uses a novel optical element called a holographic diffuser to linearize the response of the PS to wavefront tilt. The results of calibrating the sensor are given as well as caveats to the use of such a device. The results of using the Id PS to measure a static aberration as well as spatial and temporal characterization of turbulence produced by the UVIC A0 lab's Hot-Air Turbulence Generator are given.

The intent of this study is to reveal essential elements learned by reflecting and analyzing the applied design process in developing a specialized garment for a child with Spinal Muscular Atrophy (SMA). I researched and determined the clothing needs of one child with SMA, designed and created a pair of adaptive pants based on the needs of the child, tested the final product through a trial wear of the adaptive pants, and I evaluated and revised the adaptive pants. Through this study I also determined ways in which my design process can inform my teaching of applied design in my elementary art classroom.

[pt] Este trabalho é um estudo sobre o desempenho de um enlace típico do padrão UMTS/WCDMA para sistemas celulares de terceira geração, utilizando a técnica denominada modulação adaptativa. Esta técnica consiste em escolher, para cada quadro de bits transmitido, a modulação mais adequada às condições do canal. Os aspectos básicos do problema foram formulados analiticamente considerando a transmissão com modulações PSK e QAM coerentes em um canal com desvanecimento plano e efeito Doppler. Para considerar a aplicação a um modelo mais realista, foi desenvolvido um programa de simulação capaz de modelar esse mesmo problema considerando os principais componentes do sistema HSDPA (High Speed Data Packet Access), um sub-sistema do UMTS/WCDMA padronizado para transmissão de dados em alta velocidade no enlace de descida. O desempenho do enlace foi avaliado para diversas situações através da taxa de erro de bit, da taxa de transmissão média e da vazão obtida na transmissão, procurando-se investigar a influência de parâmetros do sistema nesse desempenho. / [en] This work is a study about the performance of a typical UMTS/WCDMA link for third generation mobile communications systems which uses the adaptive modulation technique. This technique consists of choosing, for each transmitted frame, the most efficient modulation according to the channel conditions. The basic aspects of the problem were analytically examined considering transmissions with PSK and QAM coherent techniques in a flat fading channel with Doppler effect. A simulator was developed in order to consider the application in a more realistic model. This simulator was capable of modeling this problem considering the main aspects of the HSDPA (High Speed Data Packet Access) system, which is a subsystem of UMTS/WCDMA that is standardized for high-speed data transmission in the downlink. The link level performance was evaluated for many different situations through average transmission bit error rate and throughput, investigating the influence of the system parameters in this performance.

The main theme of this thesis is the control of acoustic echoes for modem voice communication systems by means of echo cancellation. Two important issues in acoustic echo cancellation, namely the efficient adaptation of the echo cancellation filter and the reliable adaptation of the echo cancellation filter in double talk environment, are investigated. The delayless subband adaptive filter architecture is studied. Efficient implementation of the analysis filter bank and the time domain filtering are derived. The transforming of the subband filter weights to a fullhand counterpart is examined. It is shown that the weight transform is a synthesis filtering procedure. Two new weight transform schemes that deliver substantial performance improvements are proposed. The open-loop optimal subband filter impulse responses are shown to be non-causal and several anti-causal laps in the subband filters are required to model this non-causality. Because of the inevitable double talk detection errors, adaptive filtering algorithms with built-in double talk robustness measures are needed for the reliable operation of the echo canceller. The basic idea of robust adaptive filtering is examined. A comparison of different existing time domain robust adaptive filtering algorithms demonstrates that excellent trade-off between the convergence and the tracking properties and the double talk robustness of the adaptive filtering algorithm can he achieved by using Huher’s method for both the update of the echo cancellation filter and the estimation of scale. A delayless closed-loop robust sub- hand adaptive filter is proposed. / By independently adapting the scale estimates and normalizing the adaptation in each subband, significant improvement in terms of the convergence and tracking speed over the time domain robust NLMS algorithm can be obtained without sacrificing the double talk robustness. Moreover, it is demonstrated that by using different thresholds in the update of the echo cancellation filter and the scales, the robust algorithms converge and track echo path variation as fast as their non-robust counter part while still maintaining a sufficiently low sensitivity to double talk detection errors. The application of two path adaptive filters to acoustic echo cancellation is examined. An analysis of the original two path adaptive filtering algorithm shows that it suffers from two kinds of performance degradation due to the divergence of the background filter during double talk, namely the slow tracking of echo path variation and the false filter coefficient copying after double talk. A robust two path adaptive filter is proposed to mitigate these problems.

In this work we investigate adaptive techniques which can be used to improve the performance of highly scalable video compression schemes under resolution scaling. We propose novel content adaptive methods for motion compensated 3D discrete wavelet transformation (MC 3D-DWT) of video. The proposed methods overcome problems of ghosting and non-aligned aliasing artifacts, which can arise in regions of motion model failure, when the video is reconstructed at reduced temporal or spatial resolutions. We also study schemes which facilitate simultaneous scaling of compressed video bitstreams based on both constant bit-rate and constant distortion criteria, using simple and generic scaling operations. In regions where the motion model fails, the motion compensated temporal discrete wavelet transform (MC TDWT) causes ghosting artifacts under frame-rate scaling, due to temporal lowpass filtering along invalid motion trajectories. To avoid ghosting artifacts, we adaptively select between different lowpass filters, based on a local estimate of the motion modelling accuracy. Experimental results indicate that the proposed adaptive transform substantially removes ghosting artifacts while also preserving the high compression efficiency of the original MC TDWT. We also study the impact of various MC 3D-DWT structures on spatial scalability. Investigating the interaction between spatial aliasing, scalability and energy compaction shows that the t+2D structure essentially has higher compression efficiency. However, where the motion model fails, structures of this form cause non-aligned aliasing artifacts under spatial scaling. We propose novel adaptive schemes to continuously adapt the structure of MC 3D-DWT based on information available within the compressed bitstream. Experimental results indicate that the proposed adaptive structure preserves the high compression efficiency of the t+2D structure while also avoiding the appearance of non-aligned aliasing artifacts under spatial scaling. To provide simultaneous rate and distortion scaling, we study ???layered substream structure. Scaling based on distortion generates variable bit-rate traffic which satisfies the desired average bit-rate and is consistent with the requirements of leaky-bucket traffic models. We propose a novel method which also satisfies constraints on instantaneous bit-rate. This method overcomes the weakness of previous methods with small leaky-bucket buffer sizes. Simulation results indicate promising performance with both MC 3D-DWT interframe and JPEG2000 intraframe compression.

Thesis (M.S.)--University of Missouri--Rolla, 2007. / Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed December 3, 2007) Includes bibliographical references (p. 65-66).

Increasing densities on magnetic data storage devices leads to problems of severe intersymbol interference (ISI), additive noise and non-linearities. Advanced detection strategies for magnetic recording channels fall into two categories: partial response equalization with maximum likelihood decoding and decision feedback equalization. This study focuses on doing an adaptive all-pass forward filter for the decision feedback channel. The decision feedback channel can be equalized by a low-order continuous-time filter, and does not require a transversal filter with high-precision multiplication. This results in considerable savings in both power consumption and chip die area. One problem that has yet to be addressed is how to adaptively set the coefficients of the all-pass filter. This thesis examines the design and performance of an adaptive all-pass filter. The performances in terms of the mean-squared error (MSE) of a first- and second-order all-pass are evaluated. They are compared to a conventional FIR filter design of various lengths. An adaptive algorithm based on the least mean-squared (LMS) error is developed and characterized over a range of storage densities. Since this does not require sampling of the filter input or any states of the forward filter, the system could be realized in continuous-time up to the decision device. Numerical simulations for various data densities and noise variances are done to verify the theoretically expected performance and the adaptation behavior of the all-pass. / Graduation date: 1997

Several adaptive filters were investigated to enhance speech auditory brainstem responses (speech ABR). The objective was to shorten the long recording time currently needed by the standard coherent averaging method to obtain acceptable performance, which has limited the clinical adoption of speech ABR. Five algorithms were implemented: Wiener Filter (WF), Steepest Descent (SD), Adaptive Noise Cancellation (ANC) based on Least-Mean-Square error (LMS) and normalized LMS error (nLMS), and a multi-adaptive cascade combination of SD and LMS. The performance of the adaptive filters was assessed on speech ABR data gathered from several subjects and compared with coherent averaging using the overall Signal-to-Noise Ratio (SNR), the local SNR around the fundamental frequency and the first formant, and Mean-Square-Error (MSE) in the time and frequency domains. The adaptive filters could reduce the time needed, by at least one order of magnitude, for obtaining comparable signal quality as that obtained with coherent averaging.