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TABLE IV Codebook size (ROM) and computational complexity of Trellis-Coded Quantization with nonlinear prediction

in unknown title
by unknown authors 2003
Cited by 5

TABLE I COMPLEXITY COMPARISON OF PROPOSED OPTIMAL SISO AND WOLF TRELLIS DECODERS FOR VARIOUS REED-SOLOMON CODES. COMPLEXITY IS MEASURED BY THE BASE-2 LOGARITHM OF REAL OPERATIONS PER CODEWORD.

in Soft-in soft-out decoding of Reed-Solomon codes based on Vardy and Be’ery’s decomposition
by Thomas R. Halford, Vishakan Ponnampalam, Alex J. Grant, Keith M. Chugg 2005
Cited by 2

TABLE I Number of distance calculations and additions per symbol (i.e., per trellis stage). The number of comparisons is always less than this number, and the computational complexity per trellis stage is always less than twice this number.

in Fast Digital Locally Monotonic Regression
by N. D. Sidiropoulos

TABLE I Number of distance calculations and integer additions per symbol (i.e., per VORCA trellis stage). The number of integer comparisons is always less than this number, and the computational complexity per VORCA trellis stage is always less than twice this number.

in The Viterbi Optimal Runlength-Constrained Approximation Nonlinear Filter
by N. D. Sidiropoulos

TABLE VIII Average spectral distortion, 2 dB outliers, codebook size (ROM) and computational complexity for Block-based Trellis Quantization of LSF parameters with SVDT

in unknown title
by unknown authors 2003
Cited by 5

TABLE VII Average spectral distortion, 2 dB outliers, codebook size (ROM) and computational complexity for Block-based Trellis Quantization (BTQ-LSFD) of LSF parameters

in Quantization of LSF Parameters Using a Trellis Modelling
by Farshad Lahouti, Amir K. Khandani

TABLE VIII Average spectral distortion, 2 dB outliers, codebook size (ROM) and computational complexity for Block-based Trellis Quantization of LSF parameters with SVDT

in Quantization of LSF Parameters Using a Trellis Modelling
by Farshad Lahouti, Amir K. Khandani

TABLE VI Average spectral distortion, 2 dB outliers, codebook size and computational complexity for interframe Block-based Trellis Quantization of LSF parameters

in unknown title
by unknown authors 2004

TABLE IX Average spectral distortion, 2 dB outliers, codebook size (ROM) and computational complexity for interframe Block-based Trellis Quantization of LSF parameters. The first column indicates the average bit-rate and the (BTQ1, BTQ2) bit-rates.

in Quantization of LSF Parameters Using a Trellis Modelling
by Farshad Lahouti, Amir K. Khandani

Table 6. Some block codes and partial unit memory convolutional codes.

in The trellis complexity of convolutional codes
by R. J. Mceliece 1996
"... In PAGE 11: ... (21) turns out to be 104 edges per encoded bit. (This code is the seventh code listed in Table6 in the Appendix.) The minimal trellis complexity of unit memory and partial unit memory convolutional codes has also been studied in [6] and [32].... ..."
Cited by 4
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