20 resultados para Second Order Differential Equation


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In traditional method to blindly extract interesting source signals sequentially, the second-order or higher-order statistics of signals are often utilized. However, for impulsive sources, both of the second-order and higher-order statistics may degenerate. Therefore, it is necessary to exploit new method for the blind extraction of impulsive sources. Based on the best compression-reconstruction principle, a novel model is proposed in this work, together with the corresponding algorithm. The proposed method can be used for blind extraction of sources which are distributed from alpha stable process. Simulations are given to illustrate availability and robustness of our algorithm.

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This paper deals with blind separation of spatially correlated signals mixed by an instantaneous system. Taking advantage of the fact that the source signals are accessible in some man-made systems such as wireless communication systems, we preprocess the source signals in transmitters by a set of properly designed first-order precoders and then the coded signals are transmitted. At the receiving side, information about the precoders are utilized to perform signal separation. Compared with the existing precoder-based methods, the new method only employs the simplest first-order precoders, which reduces the delay in data transmission and is easier to implement in practical applications.

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In this paper, we present an algorithm for the systematic calculation of Lie point symmetries for fractional order differential equations (FDEs) using the method as described by Buckwar & Luchko (1998) and Gazizov, Kasatkin & Lukashchuk (2007, 2009, 2011). The method has been generalised here to allow for the determination of symmetries for FDEs with n independent variables and for systems of partial FDEs. The algorithm has been implemented in the new MAPLE package FracSym (Jefferson and Carminati 2013) which uses routines from the MAPLE symmetry packages DESOLVII (Vu, Jefferson and Carminati, 2012) and ASP (Jefferson and Carminati, 2013). We introduce FracSym by investigating the symmetries of a number of FDEs; specific forms of any arbitrary functions, which may extend the symmetry algebras, are also determined. For each of the FDEs discussed, selected invariant solutions are then presented. © 2013 Elsevier B.V. All rights reserved.

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A study was conducted to develop an integrated process lethality model for pressure-assisted thermal processing (PATP) taking into consideration the lethal contribution of both pressure and heat on spore inactivation. Assuming that the momentary inactivation rate was dependent on the survival ratio and momentary pressure-thermal history, a differential equation was formulated and numerically solved using the Runge-Kutta method. Published data on combined pressure-heat inactivation of Bacillus amyloliquefaciens spores were used to obtain model kinetic parameters that considered both pressure and thermal effects. The model was experimentally validated under several process scenarios using a pilot-scale high-pressure food processor. Using first-order kinetics in the model resulted in the overestimation of log reduction compared to the experimental values. When the n th-order kinetics was used, the computed accumulated lethality and the log reduction values were found to be in reasonable agreement with the experimental data. Within the experimental conditions studied, spatial variation in process temperature resulted up to 3.5 log variation in survivors between the top and bottom of the carrier basket. The predicted log reduction of B. amyloliquefaciens spores in deionized water and carrot purée had satisfactory accuracy (1.07-1.12) and regression coefficients (0.83-0.92). The model was also able to predict log reductions obtained during a double-pulse treatment conducted using a pilot-scale high-pressure processor. The developed model can be a useful tool to examine the effect of combined pressure-thermal treatment on bacterial spore lethality and assess PATP microbial safety. © 2013 Springer Science+Business Media New York.

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The energy equation for turbulent flow of fiber suspensions was derived in terms of second order correlation tensors. Fiber motion of turbulent energy including the correlation between pressure fluctuations and velocity fluctuations was discussed at two points of flow field, at which the correlation tensors were the functions of space coordinates, distance between two points, and time.