According to one embodiment, a data decompression device includes: a detection circuit configured to detect a boundary between a header and a payload in a compressed stream, based on boundary information in the header; a separation circuit configured to separate the header and the payload; a first decompression circuit configured to decompress a compressed coding table in the header; and a second decompression circuit configured to decompress the payload, based on an output of the first decompression circuit.

A communication system SYS includes a transmission apparatus 1 and a reception apparatus 2. The transmission apparatus includes: a conversion unit 111 for converting a bit stream Z having a bit length b into a bit stream Y that has w−1 (w is an integer equal to or larger than 2) bit 1 and that has a bit length n (n>b); a conversion unit 112 for converting the bit stream Y into a bit stream X having a bit length t (t<n); and a Neural Network 113 that has a t input node and that outputs a value relating to a feature of a transmission signal Tx when the bit stream X is inputted thereto. The reception apparatus includes: a Neural Network 212 that has a t output node and that outputs a numerical data stream U including t numerical data when a feature of the reception signal is inputted thereto; a conversion unit 213 for converting the numerical data stream U into a numerical data stream Y′ including n numerical data; and a generation unit 214 for generating a bit stream Z′ having the bit length b by performing, on the numerical data stream U, an inverse conversion of a conversion processing performed by the conversion unit 111.

The present disclosure provides a data processing system and method. The method may include obtaining preliminary data. The method may also include generating first encoded data by compressing the preliminary data in a first encoding procedure. The method may further include determining whether a compression ratio of the first encoded data is below a compression threshold. The method may still further include generating second encoded data by compressing the preliminary data in a second encoding procedure in response to determining that the compression ratio of the first encoded data is below the compression threshold, wherein the first encoding procedure and the second encoding procedure are lossless compressions.

Decoding a bitset, each bit of the bitset corresponding to a respective value in a range of a minimum value to a maximum value, includes decoding, from a compressed bitstream, indexes of bits of the bitset, each bit of the bits having a first value. Decoding the bitset also includes setting all other bits of the bitset not decoded from the compressed bitstream to a second value. Decoding the indexes of bits of the bitset includes decoding a number of the indexes of the bits of the bitset, decoding a first index of the indexes in a first range having a first lower bound and a first upper bound, and decoding a last index of the indexes in a second range having a second lower bound and a second upper bound.

A communication apparatus includes a serializer configured to convert parallel data into serial data and output the serial data; and a deserializer configured to convert the serial data output from the serializer into parallel data and output the parallel data. The serializer is configured to add first data used for detecting unique data in the parallel data before the unique data, add second data used for detecting the unique data after the unique data, and add third data whose length is variable to each of the first data and the second data.

The present invention discloses a waveform file processing method, storage medium, and device, wherein the method comprises a storage step, and such storage step comprises the following sub-steps: obtain a waveform file that comprises at least one waveform signal; assign a basic index value based on the waveform signal, and adopt the variable-length encoding method to, in a memory, encode the said waveform file as a resolvable serialized structure; when the memory consumed by the serialized structure reaches the threshold, trigger the compression and persistence for the current serialized structure, and obtain the waveform processing file. The present invention uses a unique organization mode to locally or remotely generate a waveform file of a specific format so that the efficiency of subsequent storage, reading, and debugging based on the waveform database file of the said format is significantly improved.

An efficient adaptive seismic data flow lossless compression and decompression method, which aims at solving the problem that data occupies the storage space and affects the transmission efficiency and is used for efficiently compressing geophysical instrument data, particularly seismic data after 24-bit analog-to-digital conversion. In the method, a data flow is compressed in a lossless mode in real time, and sampling data is adaptively compressed into 1 byte or 2 bytes or 3 bytes from original 24 bits and 3 bytes in a coding manner. Besides the foregoing data ranges, other integers that can be expressed by other 24-bit integer data with symbols are required to be expressed by 4 bytes after being operated through a compression algorithm. The method has the advantages of saving a large amount of storage space and remarkably increasing the data transmission efficiency.

Representative embodiments are disclosed for a rapid and highly parallel decompression of compressed executable and other files, such as executable files for operating systems and applications, having compressed blocks including run length encoded (“RLE”) data having data-dependent references. An exemplary embodiment includes a plurality of processors or processor cores to identify a start or end of each compressed block; to partially decompress, in parallel, a selected compressed block into independent data, dependent (RLE) data, and linked dependent (RLE) data; to sequence the independent data, dependent (RLE) data, and linked dependent (RLE) data from a plurality of partial decompressions of a plurality of compressed blocks, to obtain data specified by the dependent (RLE) data and linked dependent (RLE) data, and to insert the obtained data into a corresponding location in an uncompressed file. The representative embodiments are also applicable to other types of data processing for applications having data dependencies.

Representative embodiments are disclosed for a rapid and highly parallel decompression of compressed executable and other files, such as executable files for operating systems and applications, having compressed blocks including run length encoded (“RLE”) data having data-dependent references. An exemplary embodiment includes a plurality of processors or processor cores to identify a start or end of each compressed block; to partially decompress, in parallel, a selected compressed block into independent data, dependent (RLE) data, and linked dependent (RLE) data; to sequence the independent data, dependent (RLE) data, and linked dependent (RLE) data from a plurality of partial decompressions of a plurality of compressed blocks, to obtain data specified by the dependent (RLE) data and linked dependent (RLE) data, and to insert the obtained data into a corresponding location in an uncompressed file. The representative embodiments are also applicable to other types of data processing for applications having data dependencies.

In one embodiment a system, apparatus, and method for optimizing index value lengths when indexing data items in an array of data items is described, the method including producing, at a first processor, an ordered series of index values, sending the ordered series of index values to an indexing processor, receiving, at the indexing processor, a data object including the array of data items, associating, at the indexing processor, a first part of one of the index values with a first one data item of the array of data items, associating, at the indexing processor, a second part of the one of the index values with a next one data item of the array of data items, repeating the steps of associating a first part of one of the index values and associating a second part of the one of the index values until all of the data items in the array of data items are indexed.