Results 11 to 20 of about 651,619 (74)

Estimating the HEVC Decoding Energy Using the Decoder Processing Time [PDF]

IEEE International Symposium on Circuits and Systems (ISCAS), 2015, 2022
This paper presents a method to accurately estimate the required decoding energy for a given HEVC software decoding solution. We show that the decoder's processing time as returned by common C++ and UNIX functions is a highly suitable parameter to obtain valid estimations for the actual decoding energy.
arxiv   +1 more source

Anytime Decoding by Monte-Carlo Tree Search [PDF]

arXiv, 2021
An anytime decoding algorithm for tree codes using Monte-Carlo tree search is proposed. The meaning of anytime decoding here is twofold: 1) the decoding algorithm is an anytime algorithm, whose decoding performance improves as more computational resource, measured by decoding time, is allowed, and 2) the proposed decoding algorithm can approximate the ...
arxiv  

Semi-Deterministic Subspace Selection for Sparse Recursive Projection-Aggregation Decoding of Reed-Muller Codes [PDF]

arXiv, 2022
Recursive projection aggregation (RPA) decoding as introduced in [1] is a novel decoding algorithm which performs close to the maximum likelihood decoder for short-length Reed-Muller codes. Recently, an extension to RPA decoding, called sparse multi-decoder RPA (SRPA), has been proposed [2].
arxiv  

Universal decoding for arbitrary channels relative to a given class of decoding metrics [PDF]

, 2012
We consider the problem of universal decoding for arbitrary unknown channels in the random coding regime. For a given random coding distribution and a given class of metric decoders, we propose a generic universal decoder whose average error probability is, within a sub-exponential multiplicative factor, no larger than that of the best decoder within ...
arxiv   +1 more source

Sequential Decoding of Convolutional Codes for Synchronization Errors [PDF]

arXiv, 2022
Sequential decoding, commonly applied to substitution channels, is a sub-optimal alternative to Viterbi decoding with significantly reduced memory costs. In this work, a sequential decoder for convolutional codes over channels that are prone to insertion, deletion, and substitution errors, is described and analyzed. Our decoder expands the code trellis
arxiv  

Lazy-k: Decoding for Constrained Token Classification [PDF]

arXiv, 2023
We explore the possibility of improving probabilistic models in structured prediction. Specifically, we combine the models with constrained decoding approaches in the context of token classification for information extraction. The decoding methods search for constraint-satisfying label-assignments while maximizing the total probability.
arxiv  

Neural Decoding with Optimization of Node Activations [PDF]

arXiv, 2022
The problem of maximum likelihood decoding with a neural decoder for error-correcting code is considered. It is shown that the neural decoder can be improved with two novel loss terms on the node's activations. The first loss term imposes a sparse constraint on the node's activations.
arxiv  

Cascade Decoder: A Universal Decoding Method for Biomedical Image Segmentation [PDF]

arXiv, 2019
The Encoder-Decoder architecture is a main stream deep learning model for biomedical image segmentation. The encoder fully compresses the input and generates encoded features, and the decoder then produces dense predictions using encoded features. However, decoders are still under-explored in such architectures.
arxiv  

Enhanced Quasi-Maximum Likelihood Decoding of Short LDPC Codes based on Saturation [PDF]

arXiv, 2018
In this paper, we propose an enhanced quasi-maximum likelihood (EQML) decoder for LDPC codes with short block lengths. After the failure of the conventional belief propagation (BP) decoding, the proposed EQML decoder selects unreliable variable nodes (VNs) and saturates their associated channel output values to generate a list of decoder input ...
arxiv  

Successive-Cancellation Decoding of Linear Source Code [PDF]

arXiv, 2019
This paper investigates the error probability of several decoding methods for a source code with decoder side information, where the decoding methods are: 1) symbol-wise maximum a posteriori decoding, 2) successive-cancellation decoding, and 3) stochastic successive-cancellation decoding.
arxiv