Showing papers by "Amir Dembo published in 1985"

A new approach to multipulse LPC coder design

Abstract: Two new ideas for the design of multipulse excited LPC coders are presented in this paper. The first idea relates to improving the extraction of the all-pole filter parameters by taking into account the error weighting function. This function, which takes advantage of the noise masking properties of the ear, is ignored in the conventional covariance and autocorrelation methods. The new approach leads to an iterative algorithm, in which the first iteration is essentially the covariance method. Each new iteration involves estimation of the residual and increases a likelihood function, taking into account the error weighting function. The second idea relates to improving the derivation of the excitation parameters. A recursive algorithm for the optimal choice of the i-th pulse location, given the previously obtained (i-l) pulse locations, is presented. The low complexity of the new algorithm enables its combination with a tree search algorithm, thus giving a solution which is better than the solution of the algorithms reported earlier , when the error weighting function is used

Statistical design of analysis/Synthesis systems with quantization

Abstract: A statistical model is used for the optimal design of analysis/synthesis systems which include quantization of the signals in the separate bands. Two error measures are used. One is a generalization of the usual statistical mean square error (MSE) to time-varying systems (since analysis/synthesis systems with decimation and interpolation are time varying). The second measure is the time average of the expected l 2 distance between the output of the analysis stage and the analyzed reconstructed signal. The proposed design methods are based on minimizing these error measures and shown to apply not only with the DFT but also with any linear regular transform (e.g. Hadamard, DCT). The above two error measures are shown to be equivalent for a wide class of transforms (including the DFT). The design methods is applicable to either finding an optimal synthesis window for a given analysis window, or finding an optimal analysis window for a given synthesis window. The optimal windows (filters) are obtained by solving a set of linear equations. An optimal analysis/synthesis system is obtained using an iterative algorithm which is based on alternately solving these two sets of linear equations. When no quantization is applied the new design methods coincides with previously reported methods.