958 resultados para Aesthetic Response Theory


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The performance of an adaptive filter may be studied through the behaviour of the optimal and adaptive coefficients in a given environment. This thesis investigates the performance of finite impulse response adaptive lattice filters for two classes of input signals: (a) frequency modulated signals with polynomial phases of order p in complex Gaussian white noise (as nonstationary signals), and (b) the impulsive autoregressive processes with alpha-stable distributions (as non-Gaussian signals). Initially, an overview is given for linear prediction and adaptive filtering. The convergence and tracking properties of the stochastic gradient algorithms are discussed for stationary and nonstationary input signals. It is explained that the stochastic gradient lattice algorithm has many advantages over the least-mean square algorithm. Some of these advantages are having a modular structure, easy-guaranteed stability, less sensitivity to the eigenvalue spread of the input autocorrelation matrix, and easy quantization of filter coefficients (normally called reflection coefficients). We then characterize the performance of the stochastic gradient lattice algorithm for the frequency modulated signals through the optimal and adaptive lattice reflection coefficients. This is a difficult task due to the nonlinear dependence of the adaptive reflection coefficients on the preceding stages and the input signal. To ease the derivations, we assume that reflection coefficients of each stage are independent of the inputs to that stage. Then the optimal lattice filter is derived for the frequency modulated signals. This is performed by computing the optimal values of residual errors, reflection coefficients, and recovery errors. Next, we show the tracking behaviour of adaptive reflection coefficients for frequency modulated signals. This is carried out by computing the tracking model of these coefficients for the stochastic gradient lattice algorithm in average. The second-order convergence of the adaptive coefficients is investigated by modeling the theoretical asymptotic variance of the gradient noise at each stage. The accuracy of the analytical results is verified by computer simulations. Using the previous analytical results, we show a new property, the polynomial order reducing property of adaptive lattice filters. This property may be used to reduce the order of the polynomial phase of input frequency modulated signals. Considering two examples, we show how this property may be used in processing frequency modulated signals. In the first example, a detection procedure in carried out on a frequency modulated signal with a second-order polynomial phase in complex Gaussian white noise. We showed that using this technique a better probability of detection is obtained for the reduced-order phase signals compared to that of the traditional energy detector. Also, it is empirically shown that the distribution of the gradient noise in the first adaptive reflection coefficients approximates the Gaussian law. In the second example, the instantaneous frequency of the same observed signal is estimated. We show that by using this technique a lower mean square error is achieved for the estimated frequencies at high signal-to-noise ratios in comparison to that of the adaptive line enhancer. The performance of adaptive lattice filters is then investigated for the second type of input signals, i.e., impulsive autoregressive processes with alpha-stable distributions . The concept of alpha-stable distributions is first introduced. We discuss that the stochastic gradient algorithm which performs desirable results for finite variance input signals (like frequency modulated signals in noise) does not perform a fast convergence for infinite variance stable processes (due to using the minimum mean-square error criterion). To deal with such problems, the concept of minimum dispersion criterion, fractional lower order moments, and recently-developed algorithms for stable processes are introduced. We then study the possibility of using the lattice structure for impulsive stable processes. Accordingly, two new algorithms including the least-mean P-norm lattice algorithm and its normalized version are proposed for lattice filters based on the fractional lower order moments. Simulation results show that using the proposed algorithms, faster convergence speeds are achieved for parameters estimation of autoregressive stable processes with low to moderate degrees of impulsiveness in comparison to many other algorithms. Also, we discuss the effect of impulsiveness of stable processes on generating some misalignment between the estimated parameters and the true values. Due to the infinite variance of stable processes, the performance of the proposed algorithms is only investigated using extensive computer simulations.

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The concept of radar was developed for the estimation of the distance (range) and velocity of a target from a receiver. The distance measurement is obtained by measuring the time taken for the transmitted signal to propagate to the target and return to the receiver. The target's velocity is determined by measuring the Doppler induced frequency shift of the returned signal caused by the rate of change of the time- delay from the target. As researchers further developed conventional radar systems it become apparent that additional information was contained in the backscattered signal and that this information could in fact be used to describe the shape of the target itself. It is due to the fact that a target can be considered to be a collection of individual point scatterers, each of which has its own velocity and time- delay. DelayDoppler parameter estimation of each of these point scatterers thus corresponds to a mapping of the target's range and cross range, thus producing an image of the target. Much research has been done in this area since the early radar imaging work of the 1960s. At present there are two main categories into which radar imaging falls. The first of these is related to the case where the backscattered signal is considered to be deterministic. The second is related to the case where the backscattered signal is of a stochastic nature. In both cases the information which describes the target's scattering function is extracted by the use of the ambiguity function, a function which correlates the backscattered signal in time and frequency with the transmitted signal. In practical situations, it is often necessary to have the transmitter and the receiver of the radar system sited at different locations. The problem in these situations is 'that a reference signal must then be present in order to calculate the ambiguity function. This causes an additional problem in that detailed phase information about the transmitted signal is then required at the receiver. It is this latter problem which has led to the investigation of radar imaging using time- frequency distributions. As will be shown in this thesis, the phase information about the transmitted signal can be extracted from the backscattered signal using time- frequency distributions. The principle aim of this thesis was in the development, and subsequent discussion into the theory of radar imaging, using time- frequency distributions. Consideration is first given to the case where the target is diffuse, ie. where the backscattered signal has temporal stationarity and a spatially white power spectral density. The complementary situation is also investigated, ie. where the target is no longer diffuse, but some degree of correlation exists between the time- frequency points. Computer simulations are presented to demonstrate the concepts and theories developed in the thesis. For the proposed radar system to be practically realisable, both the time- frequency distributions and the associated algorithms developed must be able to be implemented in a timely manner. For this reason an optical architecture is proposed. This architecture is specifically designed to obtain the required time and frequency resolution when using laser radar imaging. The complex light amplitude distributions produced by this architecture have been computer simulated using an optical compiler.

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The law and popular opinion expect boards of directors will actively monitor their organisations. Further, public opinion is that boards should have a positive impact on organisational performance. However, the processes of board monitoring and judgment are poorly understood, and board influence on organisational performance needs to be better understood. This thesis responds to the repeated calls to open the ‘black box’ linking board practices and organisational performance by investigating the processual behaviours of boards. The work of four boards1 of micro and small-sized nonprofit organisations were studied for periods of at least one year, using a processual research approach, drawing on observations of board meetings, interviews with directors, and the documents of the boards. The research shows that director turnover, the difficulty recruiting and engaging directors, and the administration of reporting, had strong impacts upon board monitoring, judging and/or influence. In addition, board monitoring of organisational performance was adversely affected by directors’ limited awareness of their legal responsibilities and directors’ limited financial literacy. Directors on average found all sources of information about their organisation’s work useful. Board judgments about the financial aspects of organisational performance were regulated by the routines of financial reporting. However, there were no comparable routines facilitating judgments about non-financial performance, and such judgments tended to be limited to specific aspects of performance and were ad hoc, largely in response to new information or the repackaging of existing information in a new form. The thesis argues that Weick’s theory of sensemaking offers insight into the way boards went about the task of understanding organisational performance. Board influence on organisational performance was demonstrated in the areas of: compliance; instrumental influence through service and through discussion and decision-making; and by symbolic, legitimating and protective means. The degree of instrumental influence achieved by boards depended on director competency, access to networks of influence, and understandings of board roles, and by the agency demonstrated by directors. The thesis concludes that there is a crowding out effect whereby CEO competence and capability limits board influence. The thesis also suggests that there is a second ‘agency problem’, a problem of director volition. The research potentially has profound implications for the work of nonprofit boards. Rather than purporting to establish a general theory of board governance, the thesis embraces calls to build situation-specific mini-theories about board behaviour.

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Throughout the twentieth century increased interest in the training of actors resulted in the emergence of a plethora of acting theories and innovative theatrical movements in Europe, the UK and the USA. The individuals or groups involved with the formulation of these theories and movements developed specific terminologies, or languages of acting, in an attempt to clearly articulate the nature and the practice of acting according to their particular pedagogy or theatrical aesthetic. Now at the dawning of the twenty-first century, Australia boasts quite a number of schools and university courses professing to train actors. This research aims to discover the language used in actor training on the east coast of Australia today. Using interviews with staff of the National Institute of Dramatic Art, the Victorian College of the Arts, and the Queensland University of Technology as the primary source of data, a constructivist grounded theory has emerged to assess the influence of last century‟s theatrical theorists and practitioners on Australian training and to ascertain the possibility of a distinctly Australian language of acting.