A method for data compression may include scanning input data, performing, based on the scanning, a compression operation to generate compressed data using the input data, finding, based on the scanning, a delimiter in the input data, and generating, based on a position of the delimiter in the input data, a portion of data using the compressed data. The input data may include a record, the delimiter indicates a boundary of the record, and the portion of data may include the record. The generating may include generating the portion of data based on a portion size. The portion size may be a default portion size. The portion size may be based on a default portion size and a length of a match in the input data.

Multimedia codecs (compression methods), based only on FFT (Fast Fourier Transform) have been recently proposed. These codecs use the largest points (foreground) and the most energetic bands (background). Medium quality versions are based on the largest local peaks only.

The phases can be ignored with the largest local peaks or in the background. Alternatively, sine and cosine amplitudes can be used.

This invention describes methods for giving utility to the reintroduced phases, in particular: local peaks are grouped to have a very narrow bandwidth, with the phases containing the displacements of these peaks, and we transport data and the points of the foreground in the phases of the background.

High speed communications are supported using techniques similar to OFDM (Orthogonal Frequency-Division Multiplexing). These processes are intended to be used in particular with connected objects and in the physical layers of computer networks.

The present invention aims to encode and decode a sequence of integer values by substantially assigning the number of bits of a decimal fraction value per sample. An integer converter 11 selects M selected integer values from L input integer values for a set of the L input integer values and obtains J-value selection information that specifies which of the L input integer values the M selected integer values are. Furthermore, the integer converter 11 obtains one converted integer value by reversibly converting the M selected integer value and an integer value corresponding to the J-value selection information. An integer encoder 12 encodes the converted integer value to obtain a code.

In deep learning, and in particular, for data compression for allreduce in deep learning, a gradient may be compressed for synchronization in a data parallel deep neural network training for allreduce by sharing a consensus vector between each node in a plurality of nodes to ensure identical indexing in each of the plurality of nodes prior to performing sparse encoding.

A method of compressing data is described in which the compressed data is generated by either or both of a primary compression unit or a reserve compression unit in order that a target compression threshold is satisfied. If a compressed data block generated by the primary compression unit satisfies the compression threshold, that block is output. However, if the compressed data block generated by the primary compression unit is too large, such that the compression threshold is not satisfied, a compressed data block generated by the reserve compression unit using a lossy compression technique, is output.

Data to be stored in a data block for a columnar database table may be compressed according to a multi-level compression scheme. Data to be stored in the data block may be received. The data may be compressed according a column-specific compression technique to produce compressed data. The compressed data may then be compressed according to a second compression technique different than the column-specific compression technique to produce multi-level compressed data. The multi-level compressed data may be stored in the data block. When reading from the data block, multi-level compressed data may be decompressed according to the column-specific compression technique and the default compression technique applied to the data.

A decoding device comprising a decoding unit configured to decode a tactile signal encoded for each of frequency bands. A decoding method comprising decoding a tactile signal encoded for each of frequency bands. A non-transitory storage medium encoded with instructions that, when executed by a computer, execute processing comprising decoding a tactile signal encoded for each of frequency bands.

Systems, apparatuses, and methods related to bit string conversion are described. A memory resource and/or logic circuitry may be used in performance of bit string conversion operations. The logic circuitry can perform operations on bit strings, such as universal number and/or posit bit strings, to alter a level of precision (e.g., a dynamic range, resolution, etc.) of the bit strings. For instance, the memory resource can receive data comprising a bit string having a first quantity of bits that correspond to a first level of precision. The logic circuitry can determine that the bit string having the first quantity of bits has a particular data pattern and alter the first quantity of bits to a second quantity of bits that correspond to a second level of precision based, at least in part, on the determination that the bit string has the particular data pattern.

There is provided with a data processing apparatus. An acquisition unit acquires feature plane data of a layer included in a neural network. A control unit outputs a first control signal corresponding to the layer for controlling first compression processing and a second control signal corresponding to the layer for controlling second compression processing. A first compression unit performs the first compression processing corresponding to the first control signal on the feature plane data. A second compression unit performs the second compression processing corresponding to the second control signal on the feature plane data after the first compression processing. A type of processing of the second compression processing is different from the first compression processing.

A system and method for creating firmware patch files is disclosed. The method utilizes the Executable Linkable Format file that is created when the firmware image is created. By analyzing the ELF file, the patch creation software is able to identify functions and other data in the new firmware image. The patch creation software then compares these functions to corresponding functions in the old firmware image. The method then creates an edit sequence that may be used to transform the old firmware image into the new firmware image. The edit sequence is then converted into a series of opcodes, where each opcode is followed by at least one parameter. A patch program, disposed on a network device, is able to apply the patch file to update its firmware. This method creates a smaller patch file than other popular tools.