Results 271 to 280 of about 103,799 (334)

Confidence-calibrated federated graph attention for internet of things agents under latency SLOs. [PDF]

Sci Rep
Yang D, Liu B, Wan L, Dong Q.
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An embedded deep learning framework for real-time violence detection and alert generation. [PDF]

Sci Rep
Salman M, Abbas N, Ur Rahman SI, Al Alshaikh M, Saudagar AKJ.   +4 more
europepmc   +1 more source

Variance of the root mean square value of the residuals of sine fitting in the presence of additive noise. [PDF]

Sci Rep
Alegria FAC.
europepmc   +1 more source

Two dimensional filtering to reduce the effect of quantizing noise in television

, 1962
Donald Norman Graham
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Quantization noise, linearity and spectral whitening in the LFAA quantizer

, 2016
COMORETTO, Giovanni, CHIARUCCI, Simone
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Visibility of wavelet quantization noise

IEEE Transactions on Image Processing, 1997
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.
A B, Watson, G Y, Yang, J A, Solomon, J, Villasenor   +3 more
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Quantization Noise in ADPCM Systems

IEEE Transactions on Communications, 1977
The system considered here consists of a differential pulse-code modulator (DPCM) in which the quantizer is replaced by an adaptive quantizer. Adaptation is accomplished by adjusting the stepsize at every sampling instant, depending upon the magnitude of the quantization error.
Goldstein, Lawrence H., Liu, Bede
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Quantization Noise

2008
If you are working in digital signal processing, control or numerical analysis, you will find this authoritative analysis of quantization noise (roundoff error) invaluable. Do you know where the theory of quantization noise comes from, and under what circumstances it is true?
Bernard Widrow, István Kollár
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On lattice quantization noise

Proceedings of IEEE Data Compression Conference (DCC'94), 1996
Summary: We present several results regarding the properties of a random vector, uniformly distributed over a lattice cell. This random vector is the quantization noise of a lattice quantizer at high resolution, or the noise of a dithered lattice quantizer at all distortion levels.
Zamir, Ram, Feder, Meir
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Lattice quantization noise revisited

2013 IEEE Information Theory Workshop (ITW), 2013
Dithered quantization is widely used in signal processing and coding due to its many desirable properties in theory and in practice. In this paper, we show that dither is unnecessary for Gaussian sources when the flatness factor of the quantization lattice is small. This means that the quantization noise behaves much like that in dithered quantization.
Cong Ling, Lu Gan
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