Spectral Sensing for Cognitive Radio: Estimation of Adaptive Frequency Hopping Signal

The issue of dynamic spectrum scene analysis in any cognitive radio network becomes extremely complex when low probability of intercept, spread spectrum systems are present in environment. The detection and estimation become more complex if frequency hopping spread spectrum is adaptive in nature. In this paper, we propose two phase approach for detection and estimation of frequency hoping signals. Polyphase filter bank has been proposed as the architecture of choice for detection phase to efficiently detect the presence of frequency hopping signal. Based on the modeling of frequency hopping signal it can be shown that parametric methods of line spectral analysis are well suited for estimation of frequency hopping signals if the issues of order estimation and time localization are resolved. An algorithm using line spectra parameter estimation and wavelet based transient detection has been proposed which resolves above issues in computationally efficient manner suitable for implementation in cognitive radio. The simulations show promising results proving that adaptive frequency hopping signals can be detected and demodulated in a non cooperative context, even at a very low signal to noise ratio in real time.

Luova mieli : lähikuvassa muusikoiden luomisprosessit

This work studied the creative process of musicians. The subject was chosen partly due to the attention given to creativity in social discussion. The approach was material-based, because during the work it became clear that the theoretical models describing the creative process in general did not provide adequate tools for the examination of musical creation. In this study, the creative process was defined as a process, which generated a work found by the musician novel to him or her. There were two principal research questions: 1) How does the creative process of musicians progress? 2) What makes a process creative? The main emphasis was on the first question, because the study aimed at modeling the creative process of musicians. The material for this study was collected by interviewing five professional musicians, each qualified by an expert of music to be creative. The interviews were thematically linked with each musician’s recently implemented creative process. The work generated in the process was used as a stimulant in the interview. The main themes of the interview dealt with the musician’s concrete action, cognitive functioning and affective experience during the process. Secondary themes included his or her goals as well as the factors that enhanced or inhibited the process. A material-based analysis was made of the interviews. The conceptualization and modelling of the creative process was founded on a phenomenological-hermeneutic interpretation. In addition to the primary interviews, also supplementary interviews were made in order to ensure that the description of the musician was understood correctly. Further supplementary interviews were made when the material was analyzed and results were deduced. This aimed at increasing the reliability of interpretations and conclusions. The study resulted in a four-level model representing the progress of a creative process. The levels were defined by means of the conception of state. The levels used in defining the process were 1) the state determining the potential of the process, 2) the state delimiting the process, 3) the state orienting the process, and 4) the state determined by the process. The progress of the process was described as changes taking place in the state. It was discovered that the factors having an effect on the creativity of the process were the dynamism of the process, the musician’s work in relation to his or her inner standard and the impulses that caused variation in the musician’s thinking. The interview method used in this study proved to be a very suitable tool in an examination of a creative process. Thus it may well be applicable in other research contexts associated with creative processes. The outcome of this study, the model of the progress of a creative process, should also provide a feasible basis for the examination of different kinds of creative processes. It enables a comprehensive examination of a creative process, simultaneously justifying the dynamic nature of the process.

Non-linear dynamic analysis of rotors by finite element method

Non-linear natural vibration characteristics and the dynamic response of hingeless and fully articulated rotors of rectangular cross-section are studied by using the finite element method. In the formulation of response problems, the global variables are augmented with appropriate additional variables, facilitating direct determination of sub-harmonic response. Numerical results are given showing the effect of the geometric non-linearity on the first three natural frequencies. Response analysis of typical rotors indicates a possibility of substantial sub-harmonic response especially in the fully articulated rotors widely adopted in helicopters.

The Alpha-Method Direct Transcription In Path Constrained Dynamic Optimization

Numerically discretized dynamic optimization problems having active inequality and equality path constraints that along with the dynamics induce locally high index differential algebraic equations often cause the optimizer to fail in convergence or to produce degraded control solutions. In many applications, regularization of the numerically discretized problem in direct transcription schemes by perturbing the high index path constraints helps the optimizer to converge to usefulm control solutions. For complex engineering problems with many constraints it is often difficult to find effective nondegenerat perturbations that produce useful solutions in some neighborhood of the correct solution. In this paper we describe a numerical discretization that regularizes the numerically consistent discretized dynamics and does not perturb the path constraints. For all values of the regularization parameter the discretization remains numerically consistent with the dynamics and the path constraints specified in the, original problem. The regularization is quanti. able in terms of time step size in the mesh and the regularization parameter. For full regularized systems the scheme converges linearly in time step size.The method is illustrated with examples.

Correction factors for dynamic state estimation of aggregated generators

This paper presents an approach for dynamic state estimation of aggregated generators by introducing a new correction factor for equivalent inter-area power flows. The spread of generators from the center of inertia of each area is summarized by the correction term α on the equivalent power flow between the areas and is applied to the identification and estimation process. A nonlinear time varying Kalman filter is applied to estimate the equivalent angles and velocities of coherent areas by reducing the effect of local modes on the estimated states. The approach is simulated on two test systems and the results show the effect of the correction factor and the performance of the state estimation by estimating the inter-area dynamics of the system.

Dynamic Bayesian network inferencing for non-homogeneous complex systems

Dynamic Bayesian Networks (DBNs) provide a versatile platform for predicting and analysing the behaviour of complex systems. As such, they are well suited to the prediction of complex ecosystem population trajectories under anthropogenic disturbances such as the dredging of marine seagrass ecosystems. However, DBNs assume a homogeneous Markov chain whereas a key characteristics of complex ecosystems is the presence of feedback loops, path dependencies and regime changes whereby the behaviour of the system can vary based on past states. This paper develops a method based on the small world structure of complex systems networks to modularise a non-homogeneous DBN and enable the computation of posterior marginal probabilities given evidence in forwards inference. It also provides an approach for an approximate solution for backwards inference as convergence is not guaranteed for a path dependent system. When applied to the seagrass dredging problem, the incorporation of path dependency can implement conditional absorption and allows release from the zero state in line with environmental and ecological observations. As dredging has a marked global impact on seagrass and other marine ecosystems of high environmental and economic value, using such a complex systems model to develop practical ways to meet the needs of conservation and industry through enhancing resistance and/or recovery is of paramount importance.