30 results about "Data approximation" patented technology

A computer implemented device is described that is adapted for improving memory efficiency for conducting machine learning on multi-dimensional vectors stored as specially configured data structures. The device includes network interfaces adapted for receiving data sets and communicating with data harvesting applications, as well as data storage and memory for storing the configured data structures. The multi-dimensional vectors and the system provide a data architecture that processes disparate data sets to programmatically extract features transformed from raw information, the extracted features stored in the form of data values suitable for conducting data approximations and neural network processing.

Optimizing data approximation analysis using low power circuitry including receiving a first set of data results and a second set of data results; charging a first capacitor on the circuit with a unit of charge for each of the first set of data results that indicates a positive data point; charging a second capacitor on the circuit with the unit of charge for each of the second set of data results that indicates a positive data point; applying a voltage from the first capacitor and a voltage from the second capacitor to a FET on the circuit, wherein a current flows through the FET toward an output of the circuit if the voltage on the first capacitor is greater than the voltage on the second capacitor and a difference in the voltage of the first capacitor and the second capacitor is greater than a threshold voltage of the FET.

A mobile monitoring device and related systems and methods for monitoring a condition to which an object is exposed are disclosed. The monitoring device includes a sensor module for monitoring the condition and periodically producing sensor module data relating to the condition and a microcontroller. The microcontroller includes a sensor data component for receiving the sensor module data from the sensor module and a first transceiver component for receiving network manager data from a local network manager local to the monitoring device. The microcontroller further includes an associator component for comparing the network manager data with the sensor module data and, if the network manager data approximates the sensor module data, establishing an association with the local network manager.

A spray injection analysis and nozzle configuration system is described having a user input unit that collects spray system input parameters and relays the collected parameters to a fluid performance matching unit and / or problem geometry unit for subsequent processing. The user inputs basic system parameters, including the desired spray fluid characteristics, to obtain suggested system configuration, including spray nozzle types and quantities. Accuracy of suggested spray nozzle type and configuration is increased via approximating the viscosity and / or surface tension parameters of the desired spray fluid with that of collected performance data. When a user already knows the desired spray nozzle type and associated system parameters, the user input unit routes this information to the problem geometry unit for creation of a problem geometry file, including calculation of the drop size distribution and spray velocity, and performance modeling via the fluid modeling unit.

A computer implemented device is described that is adapted for improving memory efficiency for conducting machine learning on multi-dimensional vectors stored as specially configured data structures. The device includes network interfaces adapted for receiving data sets and communicating with data harvesting applications, as well as data storage and memory for storing the configured data structures. The multi-dimensional vectors and the system provide a data architecture that processes disparate data sets to programmatically extract features transformed from raw information, the extracted features stored in the form of data values suitable for conducting data approximations and neural network processing.

The invention provides a DNA sequence query system based on shared data approximation. The system compresses DNA sequences from different archives into the same data approximation. For an interested DNA sequence, which archives the sequence exists in can be quickly inquired through the data infarct. The DNA sequence query system comprises three subsystems, namely a data preprocessing subsystem, adata approximate establishing and updating subsystem and a DNA sequence query subsystem. Useful information is extracted from a given DNA sequence; original data infringement is proposed to compress the DNA sequence data of the plurality of archives; and the DNA is inquired by utilizing the data infarct. The system can be used for DNA sequence query, and the archive library data of interest is further searched for further research by querying the archive library where the DNA of interest is located.

The present invention provides a method for extracting well seismic data based on Euclidean distance approximate matching, which includes: performing approximate seismic attribute matching, finding the coordinate point position closest to the target well, and extracting the seismic attribute value corresponding to the position approximately as the corresponding value of the target well position Seismic attribute values, and integrate all seismic attribute values ​​into an attribute set; carry out approximate matching of lithological data, through the start and end time range of the time window, and use time-depth conversion to convert the time range to the depth range corresponding to the target well, and then Calculate the lithology ratio within the depth range corresponding to the target well sample; match the extracted seismic attribute set with the lithology type to obtain a seismic attribute set with category labels. This method realizes the approximation of the target well position to the nearest grid position in the adjacent distance and the extraction of the seismic data of the target well. The numerical category labels and seismic attribute values ​​can provide sample point support for the training of the machine learning classification model.

The invention discloses a suspension electromagnet posture detection system, method, computer equipment and storage medium of a maglev train. The detection data can be obtained from the same installation position, so that each detection data comes from the same position, and there is no need to approximately convert the detection data from different positions to the same position, avoiding the error caused by approximate conversion, and the detection accuracy is high; all components in the signal acquisition component start at the same time, And it is transmitted through the same channel, which ensures that all the detection data are on the same time axis, avoiding the problem of large phase error in dynamic analysis caused by different channels to obtain data, and improving the dynamic analysis. Time accuracy; and the signal conditioning and transmission module is used for data transmission instead of the vehicle CAN network, which improves the sampling frequency and sampling accuracy.

The present invention is applicable to the technical field of configuration tool application in data acquisition and monitoring control systems, and provides a method and device for quickly associating graphic elements in a graphic configuration tool. The method includes: analyzing graphic files to be associated, and obtaining all The data information of the graphic element in the graphic file; judge whether the graphic element in the graphic file has been associated; if the graphic element in the graphic file has been associated, then associate the path of the device where the graphic element is located; If the graphics entity in the graphics file has not been associated, then associate the business object of the graphics entity. The present invention can quickly complete the association of graphic elements by identifying whether the graphic elements to be associated are similar to the old associated data of the graphic elements, and quickly replace these similar graphic elements with the old associated data, thereby saving a lot of time, and is especially suitable for If there are already old graphs, you can quickly complete the association of primitives by only modifying the device path of the associated primitives, thus saving a lot of time.

The invention provides a data-driven wind farm energy storage capacity planning method, which relates to the technical field of new energy power generation planning. First, collect relevant data such as wind power, energy storage devices, wind curtailment upper limit, transmission line capacity, etc., and then establish a wind farm operation optimization model with energy storage and a wind farm energy storage capacity optimization model based on distribution robust optimization. The energy storage capacity optimization model is converted into the form of mixed integer linear programming, and finally solved by a mathematical programming solver. The wind farm energy storage capacity planning method based on distribution robust optimization provided by the invention can make full use of the historical data of wind power, consider the error of the approximate probability distribution of the historical data, take into account the economy and conservatism, and is easy to program to find the optimal solution.

Optimizing data approximation analysis using low power circuitry including receiving a plurality of data bits each corresponding to a binary indication of a test result; placing each of the plurality of data bits on an approximation circuit, wherein each of the data bits is placed on the approximation circuit by applying, to a first capacitor during a set time period, a voltage corresponding to the data bit, and wherein placing each of the plurality of data bits on the approximation circuit results in a resulting voltage stored on the first capacitor; and determining a potential correlation of the test results by comparing the resulting voltage to a voltage threshold.

The invention discloses a high-dynamic weak 8PSK / 16PSK signal carrier acquisition method, which has the advantages of high precision of the acquisition result and good real-time performance. The present invention is realized by the following technical solutions: the filtering and sampling module first performs filtering and sampling processing on the received signal, and writes the data into the data ping-pong buffer space in positive order; the data processing unit reads the ping-pong buffer data in reverse order from the data buffer space of the ping-pong buffer module; The rate compensation module performs carrier Doppler frequency change rate compensation on the sampled data, and sends the accumulated results to the FFT module for time-frequency transformation operations; the incoherent integration module approximates the absolute value of the complex data after time-frequency transformation, and then performs non-coherent integration. Coherent integration; the spectral windowing module performs cosine windowing and smoothing on the data after incoherent integration; the threshold median module combines the integration results to determine whether the capture is successful or not; the solution correction module corrects according to the median result and the Doppler rate of change Obtain the carrier Doppler at the current moment to complete the carrier acquisition.

A zombie network discovery method based on non-parameter statistics comprises the following steps: step 1, establishing a non-parameter scanning statistics model; step 2, tree priori: graph structuredata are approximated into a tree structure form convenient to process, and the tree structure adopted by the approximation mode comprises a width-first search tree, a random scanning spanning tree and a Steiner tree; and step 3, discovering the zombie network through multilayer dynamic programming based on tree priori.