Results 151 to 160 of about 3,221,012 (201)

Numerical chaos, roundoff errors, and homoclinic manifolds

Physical Review Letters, 1993
The focusing nonlinear Schr\"odinger equation is numerically integrated over moderate to long time intervals. In certain parameter regimes small errors on the order of roundoff grow rapidly and saturate at values comparable to the main wave. Although the constants of motion are nearly preserved, a serious phase instability (chaos) develops in the ...
, Ablowitz, , Schober, , Herbst
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Roundoff errors for polynomial evaluation by a family of formulae

Computing, 2008
The classical Lagrange interpolation formula is rewritten in the barycentric form. The authors show that these kind of formulas can be analyzed by making a distinction between the first steps corresponding to computations to high relative accuracy and the final sum, where high relative accuracy cannot be ensured.
Jesús M. Carnicer, Tim N. T. Goodman, Juan Manuel Peña 0001   +2 more
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Roundoff errors in block-floating-point systems

IEEE Transactions on Signal Processing, 1996
Block-floating-point representation is a special case of floating-point representation, where several numbers have a joint exponent term. In this paper, roundoff errors in signal processing systems utilizing block-floating-point representation are studied. Special emphasis is on analysis of quantization errors when data is quantized to a block-floating-
Kari Kalliojärvi, Jaakko Astola
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A roundoff error analysis of the Oja's subspace rule

1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2002
This paper deals with the effects of finite precision data representation and arithmetic in principal component analysis (PCA) networks. PCA or Karhunen Loeve transform (KLT) is a statistical method that determines an optimal linear transformation of input vectors of a stationary stochastic process.
Tamás Szabó, Gábor Horváth 0001
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Fixed-point roundoff error analysis of the RLS algorithm with time-varying channels

IEEE International Conference on Acoustics, Speech, and Signal Processing, 1991
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.
T. Adalı, S. Ardalan
semanticscholar   +1 more source

Avoiding Roundoff Error in Backpropagating Derivatives

1998
One significant source of roundoff error in backpropagation networks is the calculation of derivatives of unit outputs with respect to their total inputs. The roundoff error can lead result in high relative error in derivatives, and in particular, derivatives being calculated to be zero when in fact they are small but non-zero.
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An approach to eliminate roundoff errors in digital filters

ICASSP '78. IEEE International Conference on Acoustics, Speech, and Signal Processing, 1979
"Second-order quantizers" are introduced which can be used for implementing recursive digital filters with practically no roundoff errors or limit-cycle oscillations. Based on the idea of changing the transfer function used to compute roundoff errors, these quantizers save the low-order bits to correct the product at future iterations. For several pole
Ahmad I. Abu-El-Haija, Allen M. Peterson
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Roundoff error analysis of the pipelined ADPCM coder

1993 IEEE International Symposium on Circuits and Systems, 2002
Roundoff error analysis of a pipelined adaptive differential pulse code modulation (ADPCM) coder is presented. The pipelined coder has been developed by employing the relaxed look-ahead technique. It is shown that the precision of the quantized prediction error and those of the predictor coefficients are critical.
Naresh R. Shanbhag, Keshab K. Parhi
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Roundoff error analysis of the PCA networks

IEEE Instrumentation and Measurement Technology Conference Sensing, Processing, Networking. IMTC Proceedings, 2002
This paper deals with some of the effects of finite precision data representation and arithmetics in principal component analysis (PCA) neural networks. The PCA networks are single layer linear neural networks that use some versions of Oja's learning rule.
T. Szabo, G. Horvath
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Comments on "Roundoff Errors in Signal Averaging Systems"

IEEE Transactions on Biomedical Engineering, 1987
In this paper1 the author finds the degradation in signal-to-noise ratio (SNR) of a signal averaging system output as a function of A/D bits. The results stated are based on certain assumptions which do not hold for low values of A/D bits. Under these conditions the results seriously overestimate the SNR degradation.
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