A data storage device includes at least one data storage medium and a controller that is operably coupled to the at least one data storage medium. The controller receives the bit stream in a data storage device and performs a first level of compression on the received bit stream to obtain a symbol frame including a plurality of symbols. The controller encodes an initial portion of the plurality of symbols contained in the symbol frame by a fixed encoding scheme. The controller also collects statistics for the initial portion of the symbol frame. The controller then selects at least one data compression algorithm based on the collected statistics. The controller then performs compression encoding on a remaining portion of the symbol frame with the selected at least one data compression algorithm.

A method, article comprising machine-readable instructions and apparatus that processes data systems for encoding, decoding, pattern recognition/matching and data generation is disclosed. State subsets of a data system are identified for the efficient processing of data based, at least in part, on the data system's systemic characteristics.

Methods, devices and systems enhance compression and decompression of data values when they comprise a plurality of semantically meaningful data fields. Compression is sometimes not applied to each data value as a whole, but instead to at least one of the semantically meaningful data fields of each data value, and in isolation from the other ones. Data fields can be organized that share the same semantic meaning together to accelerate compression and decompression as multiple compressors and decompressors can be used in parallel. A system can be used where methods and devices are tailored to perform compression and decompression of the semantically meaningful data fields of floating-point numbers after first partitioning further at least one of said data fields into two or a plurality of sub-fields to increase the degree of value locality and improve compressibility of floating-point values.

In a driving data analyzer, a data collector collects, from at least one vehicle, driving data sequences while each of the driving data sequences is correlated with identification data. Each driving data sequence includes sequential driving data items, and each driving data item represents at least one of a driver's operation of at least one vehicle and a behavior of the at least one vehicle based on the at least one of a driver's operation. The identification data represents a type of at least one external factor that contributes to variations in the driving data items. A feature extractor applies a data compression network model to the driving data sequences to thereby extract, from the driving data sequences, at least one latent feature independently from the type of the at least one external factor.

In one example, a device for accessing image data includes a memory configured to store image data and one or more processors configured to code a plurality of bit length values for a plurality of block fixed length code length (bflc_len) values for a plurality of blocks of a tile or sub-tile of an image, the bit length values representing numbers of bits used to code the blfc_len values, code the bflc_len values for each of the plurality of blocks such that the bflc_len values have numbers of bits indicated by the respective bit length values, code the codewords for each of the plurality of blocks such that the codewords have the numbers of bits indicated by the bflc_len values for corresponding blocks of the plurality of blocks, and access the bit length values, the bflc_len values, and the codewords in the memory.

In one example, a device for accessing image data includes a memory configured to store image data and one or more processors configured to code a plurality of bit length values for a plurality of block fixed length code length (bflc_len) values for a plurality of blocks of a tile or sub-tile of an image, the bit length values representing numbers of bits used to code the blfc_len values, code the bflc_len values for each of the plurality of blocks such that the bflc_len values have numbers of bits indicated by the respective bit length values, code the codewords for each of the plurality of blocks such that the codewords have the numbers of bits indicated by the bflc_len values for corresponding blocks of the plurality of blocks, and access the bit length values, the bflc_len values, and the codewords in the memory.

A method, system, and computer readable medium for improved decoding CABAC encoded media are described. A decoding loop includes decoding an encoded binary element from a sequence of encoded binary elements to generate a decoded binary element using a context probability. A next context probability for a next encoded binary element in the sequence is determined from the decoded binary element and the next context probability for decoding the next encoded binary element is provided to the decoding loop for a next iteration.

In a data compression method, a computing device determines a compression feature value of to-be-compressed data based on a first parameter that affects a compression result of the to-be-compressed data. The computing device determines, based on the compression feature value, a compression policy for compressing the to-be-compressed data. The computing device then compresses the to-be-compressed data according to the compression policy to obtain compressed data, and stores the compressed data.

This application relates to the field of artificial intelligence, and discloses a data encoding method, a data decoding method, and data processing apparatuses. Both the data encoding method and the data decoding method relate to an invertible flow-based model. The invertible flow-based model includes a target invertible flow layer, a model parameter of the target invertible flow layer is used to constrain an auxiliary variable generated in an inverse transform processing process, an operation corresponding to the target invertible flow layer includes a multiplication operation and a division operation that are determined based on the model parameter, and the auxiliary variable is an increment of a product of the multiplication operation or a remainder generated through the division operation.

This disclosure provides methods, devices, and systems for data compression and decompression. The present implementations more specifically relate to entropy encoding and decoding techniques for keeping a state variable within upper and lower bounds using a noniterative process. The entropy encoding uses a fixed state threshold to determine a number of bits to remove and removes the bits from a current state prior to encoding a symbol with the current state. The entropy decoding decodes encoded data in a bitstream based on a current state to obtain the symbol and a new state and determines a number of bits to read from the bitstream and to add to the new state to update the current state.