Skip to search formSkip to main contentSkip to account menu

Context mixing

Known as: Context-mixing 
Context mixing is a type of data compression algorithm in which the next-symbol predictions of two or more statistical models are combined to yield a… 
Wikipedia (opens in a new tab)

Related topics

Related topics

12 relations
AlgorithmData compressionDynamic Markov compressionGenetic algorithm

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2019
2019
Context Mixing via Ground State Search.
To address context mixing problem via ground state search, we introduce an effective Hamiltonian whose ground state presents the… 
2017
2017
Reducing CAN latencies by use of weak synchronization between stations
Scheduling frames with offsets has been shown in the literature to be very beneficial for reducing response times in real-time… 
2017
2017
Performance of Green Leafy Vegetable Crops under Ailanthus Excelsa Based Silvihorticultural System in Western Zone of Tamil Nadu
Vegetables constitute an important component of a balanced diet for man. Indian horticulture achieves a significant increase in… 
2016
2016
Single chains to represent groups of objects
2015
2015
Komprese pomocí algoritmu Context-Mixing
Algoritmy založene na principu michani kontextů patři v soucasne době mezi ty, ktere při kompresi dosahuji těch nejlepsich v… 
2013
2013
Fast Autocorrelated Context Models for Data Compression
A method is presented to automatically generate context models of data by calculating the data's autocorrelation function. The… 
2013
2013
Delta encoding based data compression for coastal radar
Compression method for coastal radar data is developed for reducing the amount of data to meet the storage and transmission… 
2012
2012
EEDC image compression using Burrows-Wheeler data modeling
This article analyses possibilities of preparing input image data to achieve high compression ratio by using edge enhancing… 
2010
2010
In the Realm of Feathers and Fur
2010
2010
Predicting pattern-based time series using models derived from statistical data compression
This paper investigates the possibility of transferring forecasting methods motivated by data compression into the domain of… 
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy (opens in a new tab), Terms of Service (opens in a new tab), and Dataset License (opens in a new tab)