Methods, systems, and apparatus, including computer-readable storage media for hardware compression and decompression. A system can include a decompressor device coupled to a memory device and a processor. The decompressor device can be configured to receive, from the memory device, compressed data that has been compressed using an entropy encoding, process the compressed data using the entropy encoding to generate uncompressed data, and send the uncompressed data to the processor. The system can also include a compressor device configured to generate, from uncompressed data, a probability distribution of codewords, generate a code table from the probability distribution, and compress incoming data using the generated code table.

An encoding apparatus includes a memory and a processor configured to acquire text data, specify a first dynamic dictionary among a plurality of dynamic dictionaries based on attribute information of a first word included in the text data, register the first word in association with a first dynamic code in the first dynamic dictionary, and encode the first word into the first dynamic code.

An apparatus for encoding directional audio coding parameters comprising diffuseness parameters and direction parameters having a parameter calculator (100) for calculating the diffuseness parameters with a first time or frequency resolution and for calculating the direction parameters with a second time or frequency resolution; and a quantizer and encoder processor (200) for generating a quantized and encoded representation of the diffuseness parameters and the direction parameters.

Optimized memory usage and management is crucial to the overall performance of a neural network (NN) or deep neural network (DNN) computing environment. Using various characteristics of the input data dimension, an apportionment sequence is calculated for the input data to be processed by the NN or DNN that optimizes the efficient use of the local and external memory components. The apportionment sequence can describe how to parcel the input data (and its associated processing parameters—e.g., processing weights) into one or more portions as well as how such portions of input data (and its associated processing parameters) are passed between the local memory, external memory, and processing unit components of the NN or DNN. Additionally, the apportionment sequence can include instructions to store generated output data in the local and/or external memory components so as to optimize the efficient use of the local and/or external memory components.

Aspects relate to compression of messages in a wireless communication system. For messages, such as ACK/NACK feedback in a communication system, messages having an occurrence above or below a certain number of events (e.g., ACK/NACK events) or a probability of the occurrence may be compressed into a single message. By compressing the messages into a single message, the overhead used to transmit such messages may be reduced.

There is provided a computer implemented method of compressing a baseline dataset comprising a sequence of a plurality of instances of a plurality of unique data elements, the method comprising: providing a weight function that calculates an increasing value for a weight for each one of the plurality of instances of each one of the plurality of unique data elements in the baseline dataset, as a function of increasing number of previously processed sequential locations of each of the plurality of instances of each respective unique data element within the baseline dataset relative to a current sequential location of the baseline dataset, computing an encoding for the baseline dataset according to a distribution of the weight function computed for the plurality of unique data elements in the baseline dataset, and creating a compressed dataset according to the encoding.

An audio decoder for providing a decoded audio information on the basis of an encoded audio information is configured to obtain decoded spectral values on the basis of an encoded information representing the spectral values. The audio decoder is configured to jointly decode two or more most significant bits per spectral value on the basis of respective symbol codes for a set of spectral values using an arithmetic decoding, wherein a respective symbol code represents two or more most significant bits per spectral value for one or more spectral values. The audio decoder is configured to decode one or more least significant bits associated with one or more of the spectral values in dependence on how much least significant bit information is available, such that one or more least significant bits associated with one or more of the spectral values are decoded.

In accordance with an embodiment, the method includes determining a second sequence of numbers of digits for encoding the respective integer coefficient values of the first sequence, the second sequence including, as first element, a first number of digits for encoding the first integer coefficient value of the first sequence, and as second and subsequent elements, constrained numbers of digits that are greater than or equal to respective minimum required numbers of digits for encoding the second and subsequent integer coefficient values of the first sequence. The constrained numbers of digits are such that any two successive elements of the second sequence do not differ from each other by more than a given threshold value. The method further includes encoding difference values between the successive elements of the second sequence; and encoding the integer coefficient values of the first sequence using the respective numbers of digits of the second sequence.

The present invention realizes a storage device that has a high data reduction effect without decreasing I/O performances. The storage device includes a processor, an accelerator, a memory, and a storage medium, the processor specifies data to be compressed that is data stored in the storage medium from data stored in the memory and transmits a compression instruction including information relating to the data to be compressed to the accelerator, and the accelerator reads the plurality of continuous items of data from the memory and compresses the plurality of items of data to be compressed obtained by excluding data that is not to be compressed from the plurality of items of data, based on the information relating to the data to be compressed received from the processor, to generate compressed data stored in the storage device.

Lossy methods and hardware for compressing data and the corresponding decompression methods and hardware are described. The lossy compression method comprises dividing a block of pixels into a number of sub-blocks and then analysing, for each sub-block, and selecting one of a candidate set of lossy compression modes. The analysis may, for example, be based on the alpha values for the pixels in the sub-block. In various examples, the candidate set of lossy compression modes comprises at least one mode that uses a fixed alpha channel value for all pixels in the sub-block and one or more modes that encode a variable alpha channel value.