7 results about "Linear prediction coding" patented technology

The invention provides a voice packet loss hiding method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the framing processing of a received voice signal, and obtaining a current frame signal and a historical reference frame signal; based on the current frame signal, calculating an LPC coefficient through linear predictive coding LPC analysis; performing echo detection on the current frame signal and the historical reference frame signal, and judging whether an echo exists in the current frame signal; if it is judged that the echo exists, echo cancellation processing is started, and an LPC coefficient is updated based on an echo cancellation result to obtain an updated LPC coefficient; the updated LPC coefficient is used for frame reconstruction when subsequent voice packet loss occurs. According to the invention, through real-time echo detection and elimination of echo components in the reconstructed voice, the core problem of echo generation due to limitation of an LPC model in a transient phase is solved in a targeted manner, so that the reconstructed voice is purer and more natural, and the voice quality is remarkably improved.

A linear prediction coding (LPC) parameter coding method is provided. The method includes: determining a reference LPC parameter from a plurality of LPC parameters, performing direct coding on the reference LPC parameter, and performing reference coding on a non-reference LPC parameter based on the determined LPC parameter. The method includes: obtaining a direct coding result of the reference LPC parameter and determining a residual coding result of the non-reference LPC parameter.

The invention relates to the technical field of voiceprint identification, and particularly discloses a popular music singer style identification method and system based on voiceprint recognition, and the method comprises the steps: carrying out the sound source separation of a popular music audio file, and carrying out the end point detection segmentation of a separated pure human voice track, and obtaining continuous sound production segments; performing linear predictive coding analysis on the continuous sounding segments to obtain sound channel response parameters; performing recursive feature decoupling on the sound channel response parameters to obtain a sound channel cepstrum feature sequence; mapping the sound channel cepstrum feature sequence to a high-dimensional space, and performing chaos invariant estimation on a phase space trajectory obtained by mapping to obtain a double-parameter chaos feature; performing similarity comparison on the double-parameter chaos features to identify styles and genres of singers in the popular music audio file; according to the invention, the efficiency of identifying the style of the popular music singer based on voiceprint recognition can be improved.

The application relates to the technical field of network security, and provides a blockchain network attack detection method, device, equipment, medium and program product, which comprises the following steps: acquiring network access behaviors between blockchain nodes, extracting network access features from the network access behaviors and constructing a network access feature set; determining linear predictive coding spectrum features of the network access feature set according to preset network access targets and time slices; inputting the linear predictive coding spectrum features into a time sequence prediction network, taking an output state of the time sequence prediction network as a time sequence evolution mode feature of the network access targets; and performing network attack detection according to the time sequence evolution mode feature. The application can adapt to rapid dynamic changes of network attack modes by determining the time sequence evolution mode feature of the network access targets through the linear predictive coding spectrum features of the network access feature set, so that the precision of network attack detection and identification is improved.

The invention provides a control method of a liquid cooling system and electronic equipment, and can be applied to the technical field of heat dissipation. The control method of the liquid cooling system comprises the following steps: determining load grade information of electronic equipment in a target time period according to performance index data of the electronic equipment in the target time period; preprocessing the target data to obtain a plurality of sub-target data frames; performing linear predictive coding on the plurality of sub-target data frames to obtain a plurality of sub-linear predictive coefficients; based on the load level information, matching reference data from a preset health reference library; comparing the plurality of sub-target data frames and the plurality of sub-linear prediction coefficients with the matched reference data, and determining residual energy and coefficient distance corresponding to the target data; and determining a health index based on the residual energy and the coefficient distance corresponding to the target data, and generating early warning information based on the health index and a preset health threshold, the early warning information being used for prompting to perform a control operation corresponding to the early warning information on the liquid cooling system.

This application provides a control method and electronic device for a liquid cooling system, which can be applied to the field of heat dissipation technology. The control method includes: determining the load level information of the electronic device within a target time period based on performance index data; preprocessing the target data to obtain multiple sub-target data frames; performing linear prediction encoding on each of the multiple sub-target data frames to obtain multiple sub-linear prediction coefficients; matching benchmark data from a preset health benchmark library based on the load level information; comparing the multiple sub-target data frames and multiple sub-linear prediction coefficients with the matched benchmark data to determine the residual energy and coefficient distance corresponding to the target data; determining health indicators based on the residual energy and coefficient distance corresponding to the target data; generating early warning information based on the health indicators and a preset health threshold; and using the early warning information to prompt control operations corresponding to the early warning information on the liquid cooling system.