4 resultados para linear differential inclusions
em Cambridge University Engineering Department Publications Database
Resumo:
This paper presents the analysis and design of a new low power and highly linear mixer topology based on a newly reported differential derivative superposition method. Volterra series and harmonic balance are employed to investigate its linearisation mechanism and to optimise the design. A prototype mixer has been designed and is being implemented in 0.18μm CMOS technology. Simulation shows this mixer achieves 19.7dBm IIP3 with 10.5dB conversion gain, 13.2dB noise figure at 2.4GHz and only 3.8mW power consumption. This performance is competitive with already reported mixers.
Resumo:
We present the results of a computational study of the post-processed Galerkin methods put forward by Garcia-Archilla et al. applied to the non-linear von Karman equations governing the dynamic response of a thin cylindrical panel periodically forced by a transverse point load. We spatially discretize the shell using finite differences to produce a large system of ordinary differential equations (ODEs). By analogy with spectral non-linear Galerkin methods we split this large system into a 'slowly' contracting subsystem and a 'quickly' contracting subsystem. We then compare the accuracy and efficiency of (i) ignoring the dynamics of the 'quick' system (analogous to a traditional spectral Galerkin truncation and sometimes referred to as 'subspace dynamics' in the finite element community when applied to numerical eigenvectors), (ii) slaving the dynamics of the quick system to the slow system during numerical integration (analogous to a non-linear Galerkin method), and (iii) ignoring the influence of the dynamics of the quick system on the evolution of the slow system until we require some output, when we 'lift' the variables from the slow system to the quick using the same slaving rule as in (ii). This corresponds to the post-processing of Garcia-Archilla et al. We find that method (iii) produces essentially the same accuracy as method (ii) but requires only the computational power of method (i) and is thus more efficient than either. In contrast with spectral methods, this type of finite-difference technique can be applied to irregularly shaped domains. We feel that post-processing of this form is a valuable method that can be implemented in computational schemes for a wide variety of partial differential equations (PDEs) of practical importance.