62 resultados para Sound recording industry
Resumo:
Noise-predictive maximum likelihood (NPML) is a well known signal detection technique used in partial response maximum likelihood (PRML) scheme in 1D magnetic recording channels. The noise samples colored by the partial response (PR) equalizer are predicted/ whitened during the signal detection using a Viterbi detector. In this paper, we propose an extension of the NPML technique for signal detection in 2D ISI channels. The impact of noise prediction during signal detection is studied in PRML scheme for a particular choice of 2D ISI channel and PR targets.
Resumo:
A finite flexible perforated panel set in a differently perforated rigid baffle is considered. The radiation efficiency from such a panel is derived using a 2-D wavenumber domain formulation. This generalization is later used to represent a more practical case of a perforated panel fixed in an unperforated baffle. The perforations are in the form of an array of uniformly distributed circular holes. A complex impedance model for the holes available in the literature is used. An averaged fluid particle velocity is derived using the continuity equation and the surface pressure is derived using an appropriate momentum equation. The discontinuity in the perforate impedance (due to different hole dimensions or perforation ratio) at the panel-baffle interface is carefully taken into account. It is found that there exists a `coupling' of different wavenumbers of the spatially mean fluid particle velocity field. The change in the resonance frequencies and the modeshapes of the panel due to the perforations is taken into account using the Receptance method. Analytical expressions for the radiated power and radiation efficiency are derived in an integral form and numerical results are presented. Several comparisons are made to understand the radiation efficiency curves. Since both the resistive and reactive components of the hole impedance are taken into account, the model is directly applicable to micro-perforated panels also. (C) 2016 Elsevier Ltd. All rights reserved.