Disclosed are a VCD vector compression method and device based on circuit toggle behaviors. The method comprises: converting a VCD format file into a current matrix model, wherein three dimensions of the current matrix model are one time dimension and two spatial dimensions; performing preliminary screening based on an overall toggle feature: dividing the current matrix into several time segments in accordance with an equal interval in the time dimension, and performing screening according to the overall toggle feature, and forming a preliminary screened current distribution matrix by the screened time segments; performing fine screening based on region toggle features: performing further screening according to local toggle features, and forming a fine screened current distribution matrix by the screened time segments; and re-outputting the fine screened current distribution matrix as a VCD format file after vector compression.

A method for data storage may be provided. The method may include storing metadata of an image file onto a first storage device. The method may include dividing image data of the image file into at least one sub-image data set. The method may also include storing each sub-image data set of the at least one sub-image data set, onto a second storage device of at least one second storage device. The method may further include storing access information of the at least one second storage device onto the first storage device.

Data compression techniques are described for saving memory space by using fewer bits to store information while achieving high fidelity. A data set may be partitioned into a plurality of regions. Locally varying numerical ranges of data values (e.g., the minimum and maximum extents) may be determined for the plurality of regions. The data in the individual regions may be encoded using a lower number of bits as interpolation values in reference to the local extents rather than being encoded using a higher number of bits as absolute values. Where there are multiple channels of data in the regions, the number of available bits for encoding the data may be dynamically allocated per region based on the relative degrees of variance in data among the multiple channels.

A method for compressing flow data, including: generating multiple line segments according to flow data and a predefined maximum error that are acquired; obtaining a target piecewise linear function according to the multiple line segments, where the target piecewise linear function includes multiple linear functions, and an intersection set of value ranges of independent variables of every two linear functions among the multiple linear functions includes a maximum of one value; and outputting a reference data point according to the target piecewise linear function, where the reference data point includes a point of continuity and a point of discontinuity of the target piecewise linear function. In this way, a maximum error, a target piecewise linear function is further determined according to the multiple line segments, and a point of continuity and a point of discontinuity of the target piecewise linear function are used to represent compressed flow data.

A method for compressing flow data, including: constructing multiple line segments according to flow data and a predefined maximum error that are acquired; obtaining a target piecewise linear function according to the multiple line segments, where the target piecewise linear function includes multiple linear functions, and an intersection set of value ranges of independent variables of every two linear functions among the multiple linear functions includes a maximum of one value; and outputting a reference data point according to the target piecewise linear function, where the reference data point includes a point of continuity and a point of discontinuity of the target piecewise linear function. In this way, a maximum error, a target piecewise linear function is further determined according to the multiple line segments, and a point of continuity and a point of discontinuity of the target piecewise linear function are used to represent compressed flow data.

A data compressing apparatus includes a polygonal line approximating circuit receiving first time series and outputs second time series by performing a polygonal line approximation process on the first time series. The polygonal line approximating circuit includes a first multiplier and a second multiplier performing multiplication having a first value calculated based on a difference between a time component of first data and a time component of second data in the time series data as input, and a third multiplier and a fourth multiplier performing multiplication having a second value calculated based on a difference between a sensor component of the first data and a sensor component of the second data as input.

A system having a downhole sensor device and a compression device to obtain a sparse representation of data in downhole telemetry applications is described. The downhole sensor device can collect sensor data while the downhole sensor device is within a borehole. The compression device is coupled to the downhole sensor device and configured to receive the sensor data. The compression device can determine a wavelet coefficient vector for at least one row of n-tuple vectors. The wavelet coefficient vector can have a sparse representation of one or more nonzero elements. The compression device can process the wavelet coefficient vector through a set of compression algorithms, and determine a minimal bit cost of the processed wavelet coefficient vector. The compression device can select a compression algorithm from the set of compression algorithms corresponding to the minimal bit cost. The compression device can generate compressed data based on the selected compression algorithm.

Example methods, apparatus, and articles of manufacture to compress telematics data are disclosed herein. An example computer-implemented method includes identifying, using one or more processors, a portion of recorded telematics data representing a physical transversal of a physical intersection of two or more road segments, wherein each road segment has an assigned unique ordinal value; identifying, using one or more processors, a first road segment on which the physical transversal entered the intersection; identifying, using one or more processors, a second road segment on which the physical transversal exited the intersection; identifying, using one or more processors, a pair of ordinal values including a first ordinal value assigned to the first road segment, and a second ordinal value assigned to the second road segment; and storing the pair of ordinal values instead of the portion of the recorded telematics data in a compressed representation of the recorded telematics data.

For compressing data, preprocessing operations are performed on raw input data. A discrete cosine transform is performed on the preprocessed data, and multiple subbands are created, where each subband represents a particular range of frequencies. The subbands are organized into multiple groups, where the multiple groups comprise a first low frequency group, a second low frequency group, and a high frequency group. A latent space representation is generated corresponding to each of the multiple groups of subbands. A first bitstream is created based on the latent space representation, and an alternate representation of the latent space is used for creating a second bitstream, enabling multiple-pass techniques for data compression. The multiple bitstreams may be multiplexed to form a combined bitstream for storage and/or transmission purposes.

The present invention concerns a method of sampling a test signal. The method comprises: acquiring (21) training signals sampled at a plurality of sampling locations; running (23) an optimization procedure for determining an index set of n indices, representing a subset of the sampling locations, that maximize a function, over the training signals, of a quality parameter representing how well a given training signal is represented by the n indices; and sampling (25) the test signal at the sampling locations represented by the n indices.