Method and system for producing variable length context models

A variably sized context model, stored in a computer readable medium, prepared by a method for determining a variably sized context model comprising:

• counting a number of occurrences of metasymbols in an input signal data formed by a context of K symbols and a currently considered symbol;
• preparing a context tree, each node having n children, the context tree having leaf nodes, each leaf node associated with a particular context derived from a path of edges and nodes leading to the leaf node from a root node of the context tree;
• pruning the context tree by an ordered sequence of merge operations that each merges the children of a merge-candidate node;
• and
• storing the pruned context tree in the computer-readable medium for subsequent use as the variably sized context model in one of a data-compression system, a data-prediction system, a digital-data denoising system, and another such data-processing system that transforms input data to output data using the variably sized context model.

A computer readable medium containing executable instructions which, when executed in a processing system, causes the system to perform a method for determining a variably sized context model by:

• counting a number of occurrences of metasymbols in an input signal data formed by a context of K symbols and a currently considered symbol;
• preparing a context tree, each node having n children, the context tree having leaf nodes, each leaf node associated with a particular context derived from a path of edges and nodes leading to the leaf node from a root node of the context tree;
• pruning the context tree by an ordered sequence of merge operations that each merges the children of a merge-candidate node;
• and
• storing the pruned context tree in a computer-readable medium for subsequent use as the variably sized context model in one of a data-compression system, a data-prediction system, a digital-data denoising system, and another such data-processing system that transforms input data to output data using the variably sized context model.

A method, carried out on an electronic computer controlled by instructions of a computer program, for generating a variably sized context model from a fixed length context model expressed as a context tree of nodes, each node having n children, each child associated with a symbol of an alphabet having n symbols {a1, a2, . . . , an}, the context tree having nK leaf nodes, each leaf node associated with a context and an occurrence count, and a root node, the method comprising:

• determining, by the electronic computer, a number of desired leaf nodes;
• while the number of leaf nodes in the context tree is greater than the desired number of leaf nodes,
• selecting, by the electronic computer, a next node to merge;
• and
• merging, by the electronic computer, the next node to merge, the merged node thereafter considered to be a leaf node;
• and
• storing, by the electronic computer, the context tree in a computer-readable medium for subsequent use as the variably sized context model in one of a data-compression system, a data-prediction system, a digital-data denoising system, and another such data-processing system that transforms input data to output data using the variably sized context model.

A variably sized context model, stored in a computer readable medium, prepared by a method for generating a variably sized context model comprising:

• determining a number of desired leaf nodes;
• while the number of leaf nodes in a context tree is greater than the desired number of leaf nodes,
• selecting a next node to merge;
• and
• merging the next node to merge, the merged node thereafter considered to be a leaf node;
• and
• storing the pruned context tree in the computer-readable medium for subsequent use as the variably sized context model in one of a data-compression system, a data-prediction system, a digital-data denoising system, and another such data-processing system that transforms input data to output data using the variably sized context model.

A computer readable medium containing executable instructions which, when executed in a processing system, causes the system to perform a method for generating a variably sized context model comprising:

• determining a number of desired leaf nodes;
• while the number of leaf nodes in a context tree is greater than the desired number of leaf nodes,
• selecting a next node to merge;
• and
• merging the next node to merge, the merged node thereafter considered to be a leaf node;
• and
• storing the pruned context tree in a computer-readable medium for subsequent use as the variably sized context model in one of a data-compression system, a data-prediction system, a digital-data denoising system, and another such data-processing system that transforms input data to output data using the variably sized context model.