at the nature of the errors that result from nonrandom quantization errors in an instrument’s timebase circuit. Simulations and measurements on a sampling voltmeter show that the errors in measured rms amplitude have a nonnormal probability distribution, such that the probability of large errors is much greater

Abstract We review two versions of a new topology preserving mapping, the HaToM. This mapping has previously been investigated as a data visualization tool but, in this paper, we investigate empirically the quantization errors in both versions of the mapping. We show that the more model driven

Abstract-The principal objective of this paper is the study of the arithmetic roundoff error characteristics of several discrete Hartley transform (DHT) algorithms. We first summarize a variety of efficient DHT algorithms including Bracewell's original decimation-in-time radix-2 algorithm

The vectocardiography (VCG) is the methodological extension of electrocardiography (ECG) that allows three-dimensional imaging of the cardiac electrical field. For the lack of the sufficient technological support it was underestimated for years, and currently comes back to the clinical practice thanks to the use of numerically performed spatial transforms. The VCG signal is usually acquired with use of the pseudoorthogonal Frank leads and stored as three simultaneous signals corresponding to three Cartesian coordinates XYZ. This paper addresses the issue of the alternative format for the VCG storage: the Spherical Coordinates.

The Discrete Wavelet Transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression. Measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band

In this paper a stochastic analysis of the quantization error in a stereo imaging system has been presented. Further the probability density function of the range estimation error and the expected value of the range error magnitude are derived in terms of various design parameters. Further

is that the source samples have a "smooth" joint distribution. We give a precise statement of this property, and generalize it to non-uniform quantization and to vector quantization. We show that the quantization errors resulting from independent quantizations of dependent real random variables become

Abstract — In this paper we show that the quantization error for Dynamic Cell Structures (DCS) Neural Networks (NN) as defined by Bruske and Sommer provides a measure of the Lyapunov stability of the weight centers of the neural net. We also show, however, that this error is insufficient in itself

In this paper, we motivate and introduce a novel vector quantization (VQ) scheme for distributing the quantization error among the quantized features of a continuous feature vector in a predefined manner. This is done by defining ratios between the individual quantization errors of the features

In this Letter, we show that under the assumption of high resolution, the quantization errors of fGn and fBm signals with uniform quantizer can be treated as uncorrelated white noises. 1