Development and research methods of compression of complex signals based on optimal and suboptimalnoy processing phase response

The article provides further study of information possibilities phase response of seismic signals to improve resolution records in a thin-layered environment. In the paper, new algorithm of compression of complex signals based on optimal and sub optimal treatment of their phase response of proposed

Development and research methods of compression of complex signals based on optimal and suboptimalnoy processing phase response

The article provides further study of information possibilities phase response of seismic signals to improve resolution records in a thin-layered environment. In the paper, new algorithm of compression of complex signals based on optimal and sub optimal treatment of their phase response of proposed

Leverage effect as an indicator of borrowing feasibility oil and gas companies

The aim of this study is the analysis and evaluation of ratio between equity and debt capital of organizations, which provide the optimal proportion between the level of return on equity and the level of financial stability. The purpose of the financial policy of any organization is to maximize the return on equity, cost of capital growth and to minimize the weighted average cost of capital. The object of research is OJSC "Surgutneftegaz". The company is one of the largest companies in the Russian oil sector. On the basis of the forms of financial reporting we made the calculation of following indicators: economic profitability, financial leverage effect. The study made the forecast calculation in the three scenarios of development of enterprises under different conditions of capital financing from own and borrowed sources of financing. The use of financial leverage indicator to determine the feasibility of borrowing effect clearly demonstrated the need for adjustment of the financial policy of OJSC "Surgutneftegas". Recommendations to improve the credit policy of the organization were made

Comparative study of main deconvolution methods on sismic data

In this paper we treat a problem which occurs in différent domains : geophysics, speech processing, echography, where the goal is to characterize a propagating medium through its impulse response from a filtered and a noisy one . In seismic reflection a wave named source wavelet is emitted into the earth to detect reflections at the interfaces of geologic layers. The records or seismic traces may be considered as the linear filtering resuit of the wavelet by the earth response or reflectivity function . Deconvolution lies ln estimating the wavelet, removing its affect from the trace in order to restore the reflectivity . We present a comparative study of différent methods with simulations representing numerous situations to do more in that domain and to define a strategy in seismic data processing .Nous traitons dans cet article un problème que l'on rencontre dans des domaines aussi divers que la géophysique, le traitement de la parole ou l'échographie et qui consiste à caractériser un milieu de propagation par sa réponse impulsionnelle à partir d'une version filtrée et bruitée de cette réponse . En sismique réflexion, une onde appelée ondelette source, est émise dans le sol afin de détecter les réflexions se produisant sur les interfaces des couches géologiques . Les enregistrements ou traces sismiques représentent, en première approximation, le résultat d'un filtrage linéaire du signal source par la réponse impulsionnelle du sous-sol ou fonction de réflectivité. La déconvolution consiste, par une estimation de l'ondelette, à éliminer l'effet convolutif de cette dernière, de la trace, en vue de la restitution de la fonction de réflectivité . Comme en général, seule la trace est disponible, la solution du problème dépend des hypothèses faites a priori sur l'ondelette ou sur la fonction de réflectivité . Nous présentons une étude comparative de divers types de méthodes, sur des données simulées représentant des situations différentes, pour combler un certain vide dans ce domaine et esquisser une méthodologie à suivre dans le traitement de déconvolution des données sismiques

Signal restoration from data aliased in time

This paper deals with the problem of signal restoration from data aliased in time. The signal, which is in general noncausal, is split into a causal and an anticausal part. The causal part and the time-reversed anticausal part are then modeled as impulse responses of rational pole-zero models. The parameters of these models are then estimated by solving sets of overdetermined equations. The choice of model orders, i.e., number of poles and zeros of rational models, is also discussed. It is shown that if the aliasing period is large enough, there is sufficient information for all the parameters to be estimated. The special cases of a purely causal signal or a purely anticausal signal are discussed. Simulation results show that the signal can be recovered with excellent accuracy

Linear Predictive Spectral Analysis via the Lp Norm

This study involves linear predictive spectral analysis under the general LP norm; both one dimensional and two dimensional spectral estimation algorithms are developed. The objective in this study is determination of frequency resolution capability for various LP normed solutions to linear predictive spectral estimation equations. A modified residual steepest descent algorithm is utilized to generate the required solution. The research presented in this thesis could not have been accomplished without the support of the Oklahoma State University Research Consortium For Well Log Data Enhancement Via Signal Processing. The member companies of this consortium include Amococ Production Company, Area Oil and Gas Company, Cities Service Oil and Gas Corporation, Conoco, Exxon, IBM, Mobil Research and Development, Phillips Petroleum Corporation, Sohio Petroleum Company, and Texaco.Electrical Engineerin