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Table 5.1 CIMU Gyro Quantization Noise Estimation Results

in UNIVERSITY OF CALGARY Modeling Inertial Sensors Errors Using Allan Variance
by Haiying Hou, Haiying Hou 2004

Table 4: Largest numerical values of the worst case bounds on quantization noise for the proposed designs.

in unknown title
by unknown authors
"... In PAGE 4: ... Quantization noise is the severest in CG BJ because of the large number of multipliers that feed this output. Table4 shows the numerical values of the largest bounds on the quantization noise for the approximate DCTs with coefficient complexities of 0, 6, and 12 adders. If the input signal is scaled and the output is reduced by the largest bounds on quantization noise then only the LSB of the out- put can be contaminated by quantization noise.... ..."

Table 1: Recognition accuracy after quantization noise (SNR dB) is added to each feature.

in Joint Channel Decoding - Viterbi Recognition for Wireless Applications
by Alexis Bernard, Abeer Alwan 2001
Cited by 3

Table 4.1 Gaussian: Optimum MSE of Quantization Noise for Various Val- ues of Li

in A Study of Bit Allocation for Gaussian Mixture Model Quantizers and Image Coders
by Denis Tran 2005

Table 5.3 HG1700 Gyro Quantization Noise Estimation Results

in UNIVERSITY OF CALGARY Modeling Inertial Sensors Errors Using Allan Variance
by Haiying Hou, Haiying Hou 2004

Table 1: Comparison of different algorithms for varying noise levels and quantization

in A Survey of Planar Homography Estimation Techniques
by Anubhav Agarwal, C. V. Jawahar, P. J. Narayanan 2005
"... In PAGE 20: ...he algorithm. Our initial experiments with them give very similar results. 4.3 Homography estimation Table1 compares the performance of the above algorithms in the presence of Gaussian noise. Results for four levels of noise are shown in the table.... ..."
Cited by 2

Table 1 gives the results of an experiment in which random noise was generated depicting the quantization noise in frame L and frame H and then checking how accurately the total distortion in frames A and B can be predicted.

in Distortion Prediction For Motion-Compensated Lifted Haar Wavelet Transform and its application to Rate Allocation
by Aditya Mavlankar, Eckehard Steinbach, Technische Universität München 2004
"... In PAGE 4: ... Table1 : Validity of the distortion prediction The column Ratio 1 gives the ratio of the actual squared error in the reconstructed video to the squared error introduced in the transform domain. This depicts the sacrifice of orthonormality as the ratio deviates away from unity.... In PAGE 4: ... Two successive frames of the Foreman sequence were used for this experiment. Err Amp in Table1 denotes the amplitude of the random error added. 3.... ..."
Cited by 3

TABLE 1. QUANTIZER PERFORMANCE AT 24 BITS WITHOUT CHANNEL NOISE.

in Predictive Vq For Noisy Channel Spectrum Coding: Ar Or Ma?
by Jan Skoglund, Jan Lindén 1997
Cited by 5

Table 3 shows some of the implementation results obtained; the introduced quantization noise is well under a disturbing threshold, and the maximum operating frequency is suffi- cient for the selected oversampling rate to work. The over- sampling factor can be adjusted by properly removing the final half-band stage.

in FPGA Implementation Of A Multimodal Sample Rate Converter And Synchronizer
by Giuseppe Baruffa, Saverio Cacopardi, Simeone M. Solazzi

Table 3 PSNR and compression ratio to noise ratio dependence for image of Lena and diamond when the quantization accuracy equals 30 Noise ratio PSNR (dB) Compression ratio

in Abstract Lossy dictionary-based image compression method
by Gabriela Dudek, Przemysław Borys, Zbigniew J. Grzywna 2006
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