Topic
Average-case complexity
About: Average-case complexity is a research topic. Over the lifetime, 1749 publications have been published within this topic receiving 44972 citations.
Papers published on a yearly basis
Papers
More filters
21 Nov 2008
TL;DR: A new algorithm to simplify the Sphere-decoding of V-BLAST architecture is deduced using the system bit error ratio (BER) and complexity, which is much lower than the complexity of classical sphere-Decoding.
Abstract: In this paper, a new algorithm to simplify the Sphere-decoding of V-BLAST architecture is deduced. The system bit error ratio (BER) and complexity are simulated to compare the performance when sphere-decoding algorithm is used with the performance when classical sphere-decoding algorithm is used. According to simulation, the complexity of the modified sphere-decoding algorithm is much lower than the complexity of classical sphere-decoding.
17 Aug 2011
TL;DR: Simulation results show that the proposed algorithm causes negligible performance degradation with reduction in computational complexity for stochastic decoding of non-binary LDPC codes, which gives some advantages in hardware implementation of the decoders.
Abstract: Non-binary LDPC codes offer higher performances than their binary counterpart but suffer from highest decoding complexity. A solution to reduce the decoding complexity is the use of stochastic decoding algorithm, but the computational complexity of probability generation in the first step is very high. In this paper, we propose a simple method to fast generate the probability especially in high-order modulation schemes. Simulation results show that the proposed algorithm causes negligible performance degradation with reduction in computational complexity for stochastic decoding of non-binary LDPC codes, which gives some advantages in hardware implementation of the decoders.
TL;DR: It is shown that an algorithm polynomial on average with respect to μ that determines an optimal solution to a set cover problem that differs from the initial problem in one position of the constraint matrix does not exist if the optimal solution of the original problem is known and DistNP is not a subset of Average-P.
Abstract: It is shown that an algorithm polynomial on average with respect to μ and that determines an optimal solution to a set cover problem that differs from the initial problem in one position of the constraint matrix does not exist if the optimal solution of the original problem is known and DistNP is not a subset of Average-P. A similar result takes place for the knapsack problem.
10 Apr 2012
TL;DR: This work introduces mathematical properties for functionals that evaluate the complexity of vector quantization and shows that fundamental limits hold for the quantization trade-off between distortion, rate, and complexity.
Abstract: This work introduces mathematical properties for functionals that evaluate the complexity of vector quantization. Considering complexity functionals with such properties, it is shown that fundamental limits hold for the quantization trade-off between distortion, rate, and complexity. Part of the discussion presented in 2008 by Gray et al., [6], is extended, by replacing the original log codebook size constraint by a generalized complexity functional constraint.