The Experts below are selected from a list of 213 Experts worldwide ranked by ideXlab platform
S.h. Ardalan - One of the best experts on this subject based on the ideXlab platform.
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Fixed-point Roundoff Error analysis of the RLS algorithm with time-varying channels
[Proceedings] ICASSP 91: 1991 International Conference on Acoustics Speech and Signal Processing, 1991Co-Authors: T. Adali, S.h. ArdalanAbstract:The authors derive the steady-state mean square prediction Error expression for the fixed-point RLS (recursive least squares) algorithm for the case of time-varying channel estimation, which is modeled as a first-order Markov tapped delay line. It is shown that the random variable driving the time-varying system taps affects the prediction Error in the same way as does the Roundoff Error term due to weight update. It causes the Error to grow linearly with time when the forgetting factor, lambda , is chosen as 1. For lambda
T. Adali - One of the best experts on this subject based on the ideXlab platform.
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Fixed-point Roundoff Error analysis of the RLS algorithm with time-varying channels
[Proceedings] ICASSP 91: 1991 International Conference on Acoustics Speech and Signal Processing, 1991Co-Authors: T. Adali, S.h. ArdalanAbstract:The authors derive the steady-state mean square prediction Error expression for the fixed-point RLS (recursive least squares) algorithm for the case of time-varying channel estimation, which is modeled as a first-order Markov tapped delay line. It is shown that the random variable driving the time-varying system taps affects the prediction Error in the same way as does the Roundoff Error term due to weight update. It causes the Error to grow linearly with time when the forgetting factor, lambda , is chosen as 1. For lambda
P.w. Wong - One of the best experts on this subject based on the ideXlab platform.
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Quantization noise, fixed-point multiplicative Roundoff noise, and dithering
IEEE Transactions on Acoustics Speech and Signal Processing, 1990Co-Authors: P.w. WongAbstract:The author considers the characteristics of the Error resulting when a continuous amplitude signal x/sub n/ is quantized and then multiplied by a constant multiplier a under fixed-point Roundoff arithmetic. It is shown that the overall Error of such an operation can be decomposed into two terms: one being a scaled version of the Error due to the quantization of x/sub n/ and the other due to rounding off the product aQ(x/sub n/). Exact first- and second-order moments are derived for the quantization Error, the Roundoff Error, and the overall Error as a function of the multiplier a and the distribution of x/sub n/. Sufficient conditions are given for the quantization Error and the Roundoff Error to be individually uniformly distributed and white up to the first- and second-order moments, and also for them to be mutually uncorrelated. It is also shown that regardless of the probability distribution of the input signal x/sub n/, it is always possible to add a suitable dither signal to the input of the system so that both the quantization Error and the Roundoff Error are uniformly distributed, white, and mutually uncorrelated. For Gaussian inputs, the sufficient conditions given are not satisfied.
J.g. Proakis - One of the best experts on this subject based on the ideXlab platform.
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Comparison of order-recursive adaptive RLS algorithms
1993 IEEE International Conference on Acoustics Speech and Signal Processing, 1993Co-Authors: K. Zhao, J.g. ProakisAbstract:The finite word-length effects of the class of order-recursive least-squares algorithms are studied. The order-recursive algorithms can be modeled as arrays of interconnected cells or building blocks, which makes it possible to evaluate their numerical accuracy by studying the cell and then the combined Roundoff noise effects in the array. The Roundoff Error of the local variable in each cell is given by a state-space model. The states of this Error model are decoupled from each other: the Roundoff Error of a lower order residual (input) does not contribute significantly to the local state Error, but only propagates through each building block to the higher order residual (output). This analysis is confirmed by numerical simulation.
Yuri A Gadzhiev - One of the best experts on this subject based on the ideXlab platform.
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on the variance of a centered random value Roundoff Error
Signal Processing, 2015Co-Authors: Yuri A GadzhievAbstract:We derive two expressions for Roundoff Error variance, one for a rounded off random value with a zero mean and a given variance under uniform distribution and another for such a value under a normal. Also, an expression for truncation Error variance for values under uniform distribution is obtained. An application of the expressions to analysis of processing essentially quantized data by a nonrecursive smoothing filter is shown. Also their applications to quantization Error (quantization noise) analysis of general linear processing of quantized signals under uniform and normal distributions and to quantization Error analysis of essentially quantized discrete transforms like DFT (discrete Fourier transform), DCT (discrete cosine transform), DWT (discrete Walsh transforms), wavelet transforms, and so on, to image, sound (audio), video and to general signal processing in many cases can be considered as useful. The effect of accuracy of using these expressions is the more, the more used quantization level and the less maximal signal amplitudes. We find the means and variances of the Roundoff Errors for a centered random variable in a given range.We derive exact expressions for the variance in closed analitical form.We obtain the variance expressions for the cases of uniformly and normally distributed random values.
