An apparatus includes data acquisition circuitry and a processor. The data acquisition circuitry is configured to acquire multiple signals using multiple respective electrodes of an array of electrodes coupled to one of an organ of a patient and tissue or a cell culture. The processor is configured to hold a definition of a mixed-norm that is defined as a function of relative positions of the electrodes in the array, and jointly compress the multiple signals in a compressed-sensing (CS) process that minimizes the mixed-norm.

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.

Certain implementations of the disclosed technology may include methods and computing systems for performing high-density data compression, particularly on numerical data that demonstrates various patterns, and patterns of patters. According to an example implementation, a method is provided. The method may include extracting a data sample from a data set, compressing the data sample using a first compression filter configuration, and calculating a compression ratio associated with the first compression filter configuration. The method may also include compressing the data sample using a second compression filter configuration and calculating a compression ratio associated with the second compression filter configuration. A particular compression filter configuration to utilize in compressing the entire data set may be selected based on a comparison of the compression ratio associated with the first compression filter configuration and a compression ratio associated with the second compression filter configuration.

Certain implementations of the disclosed technology may include methods and computing systems for performing high-density data compression, particularly on numerical data that demonstrates various patterns, and patterns of patters. According to an example implementation, a method is provided. The method may include extracting a data sample from a data set, compressing the data sample using a first compression filter configuration, and calculating a compression ratio associated with the first compression filter configuration. The method may also include compressing the data sample using a second compression filter configuration and calculating a compression ratio associated with the second compression filter configuration. A particular compression filter configuration to utilize in compressing the entire data set may be selected based on a comparison of the compression ratio associated with the first compression filter configuration and a compression ratio associated with the second compression filter configuration.

A network node signals to a wireless communication device which precoders in a codebook are restricted from being used. The network node in this regard generates codebook subset restriction signaling that, for each of one or more groups of precoders, jointly restricts the precoders in the group by restricting a certain component (e.g., a certain beam precoder) that the precoders in the group have in common. This signaling may be for instance rank-agnostic signaling that jointly restricts the precoders in a group without regard to the precoders' transmission rank. Regardless, the network node sends the generated signaling to the wireless communication device.

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.

Embodiments of the present disclosure are directed to forwarding a large amount of data in a machine-to-machine (M2M) system, and a method for operating a first device may include: transmitting, to a second device, a request message for bulk data transfer; and receiving, from the second device, an acknowledgment message for notifying completion of the bulk data transfer, wherein the request message may include at least one of information for identifying data to be included in bulk data, information on a target common service entity (CSE) in a target platform that receives the bulk data, information for indicating processing of source data after the bulk data transfer, and information for accessing the target CSE.

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.

The disclosure relates to compressing strings by reducing the number of string characters that are stored. For example, a system may generate a first radix tree for a set of strings and a second radix tree for a reverse of each of the set of strings. The system may merge nodes of the first radix tree and/or second radix tree based on a tuning parameter. The system may identify, based on the first radix tree, beginning portions of at least two strings that match and identify, based on the second radix tree, ending portions of at least two strings that match. The system may use the matching beginning portions, the unique portions, and/or the matching ending portions to generate a pattern that matches the two or more strings. The system may store the two or more strings in association with the generated pattern without their matching beginning and/or ending portions.

In some implementations, a system can optimize offline map data updates. For example, a server device in the system can determine a metric for identifying map data objects based on attributes of the map data objects. The server device can then generate a quadtree that stores the map data objects in nodes of the quadtree based on the metric. When processing an update to the map data stored at the server device, the server device can generate update data describing the updates for each node in the quadtree based on a binary difference algorithm and/or a semantic difference algorithm. The server device can select the algorithm based on which algorithm results in the smallest compressed size of the update data.