A method of neural network decoding includes receiving a first syntax element in a model parameter set from a bitstream of a compressed neural network representation (NNR) of a neural network. The first syntax element indicates whether a coding tree unit (CTU) block partitioning is enabled for a tensor in an NNR aggregate unit. The method also includes reconstructing the tensor in the NNR aggregate unit based on the first syntax element.

Methods, devices and systems for signaling the use of subpictures in coded video pictures are described. One example method ofvideo processing includesperforming a conversionbetween a picture of a video and a bitstream of the video, wherein the bitstream conforms to a format rule, wherein the format rule specifies a mapping between identifiers of one or more subpictures of the picture and the one or more subpictures is not included in a picture header of the picture, and wherein the format rule further specifies that the identifiers of the one or more subpictures are derived based on syntax elements in a sequence parameter set (SPS) and a picture parameter set (PPS) referred to by the picture.

Methods for converting an n-bit number into an m-bit number for situations where n>m and also for situations where n<m, where n and m are integers. The methods use truncation or bit replication followed by the calculation of an adjustment value which is applied to the replicated number.

Provided is an encoding/decoding technique according to which it is possible to perform encoding with a small average bit count, even for a series of integer values with a distribution that is significantly biased to a small value, including small values that are not zero values. The present invention includes an integer encoding unit that, for an input series of non-negative values x.sub.n, n∈{1, 2, . . . , N} (hereinafter referred to as “integer series”), obtains a one-bit code with a bit value of “x” as a code corresponding to L consecutive integer values 0 included in the integer series, L being an integer that is 2 or more, and obtains a K×x.sub.n-bit or a K×x.sub.n+1-bit code that includes at least one bit value “x” and at least one bit value “y” in the first bit to the K-th bit and in which the bit values of the K×(x.sub.n−1) bits from the end are “y”, as a code corresponding to a set composed of 0 to L−1 consecutive integer values 0 included in the integer series and one integer value x.sub.n other than 0.

A data store system may include a storage device configured to store a plurality of data store tables. The data store system a further include a processor in communication with the storage device. The processor may receive a request to encode a column of a data store table from the plurality of data store tables. The processor may further generate a bit value representation of each value in the column of the data store table. The processor may further generate an index. The index may include an index value representative of each bit position of the bit value representations. The processor may further reorder bits of each bit value representation according to a predetermined pattern. The processor may further encode each reordered bit value representation according to an encoding technique. The processor may further store each encoded reordered bit value representations and the index. A method and computer-readable medium are also disclosed.

The present disclosure pertains to systems and methods to compress an input signal representing a parameter in an electric power system. In one embodiment, a system includes a data acquisition subsystem to receive an input signal comprising a plurality of high-speed representations of electrical conditions. A linear prediction subsystem generates an excitation signal estimate based on the input signal, a plurality of linear prediction coefficients based on the input signal, and an estimated signal based on the excitation signal estimate and the plurality of linear prediction coefficients. An error encoding subsystem may generate an encoding of an error signal based on a difference between the input signal and the estimated signal. A non-transitory computer-readable storage medium may store an encoded and compressed representation of the input signal comprising the excitation signal estimate, the plurality of linear prediction coefficients, and the encoding of the error signal.

A system comprises an encoder configured to compress attribute information for a point cloud and/or a decoder configured to decompress compressed attribute information for the point cloud. To compress the attribute information, a transform is applied to the attribute values to generate attribute coefficients/transformed attribute values. Points with attribute coefficients with a significant value are assigned a first binary flag value, while points with non-significant attribute coefficients are assigned a second binary flag value. A K.sup.th order exponential Golomb encoder or Golomb-Rice encoder is used to compress the run-length values, where separate states and associated contexts are maintained for funs of both the first and second binary values. A decoder uses a corresponding process to decode the compressed attribute information.

A system comprises an encoder configured to compress attribute information for a point cloud and/or a decoder configured to decompress compressed attribute information for the point cloud. To compress the attribute information, a transform is applied to the attribute values to generate attribute coefficients/transformed attribute values. Points with attribute coefficients with a significant value are assigned a first binary flag value, while points with non-significant attribute coefficients are assigned a second binary flag value. A K.sup.th order exponential Golomb encoder or Golomb-Rice encoder is used to compress the run-length values, where separate states and associated contexts are maintained for funs of both the first and second binary values. A decoder uses a corresponding process to decode the compressed attribute information.

A system utilizing a high throughput coding mode for CABAC in HEVC is described. The system may include an electronic device configured to obtain a block of data to be encoded using an arithmetic based encoder; to generate a sequence of syntax elements using the obtained block; to compare an Absolute-3 value of the sequence or a parameter associated with the Absolute-3 value to a preset value; and to convert the Absolute-3 value to a codeword using a first code or a second code that is different than the first code, according to a result of the comparison.

An ECG signal lossless compression system includes: a signal difference value generating module and a compression module. The signal difference value generating module performs an adaptive linear prediction encoding on an ECG signal, so as to generate a plurality of signal difference values corresponding to each datum of the ECG signal; the compression module divides the signal difference values into a plurality of groups and performs an adaptive linear lossless compression encoding on each group, so as to generate a plurality of window compression streams, wherein each group corresponds to a bit reference index configured to be a compression encoding parameter of the adaptive linear lossless compression encoding.