22 results about "Coefficient quantization" patented technology

The invention provides a TLF-GV signal correlation earthquake three-element joint probability prediction method and system, belongs to the technical field of earthquake prediction, and aims to solve the problems that traditional three-element prediction lacks joint fusion, evidence conflicts are difficult to process, and weights are fixed. Comprising the following steps: extracting physical features of TLF-GV signals, carrying out preorder three-element prediction results and model credibility parameters, splicing the physical features into feature vectors, inputting the feature vectors into a dynamic weight prediction model constructed by a shallow MLP, and outputting time, magnitude and position weights; dividing the three elements into 3 * 3 * 3 = 27'time-magnitude-position 'propositions, generating basic probability assignment (BPA) of each proposition based on weights, and quantifying evidence contradictions through a conflict coefficient K; and adopting a Dempster combination rule to obtain a joint BPA, calculating a mean value of a reliability function and a likelihood function of each proposition as a comprehensive probability, and extracting a maximum probability proposition as a coupling result. According to the method, the scientificity and practicability of strong earthquake short-term and temporary prediction are remarkably improved.

The invention relates to a low latency low frequency effect codec. In some embodiments, a method of encoding a low frequency effect (LFE) channel includes receiving a time domain LFE channel signal; filtering the time domain LFE sound channel signal by using a low-pass filter; converting the filtered time domain LFE channel signal into a frequency domain representation of the LFE channel signal comprising a number of coefficients representing a spectrum of the LFE channel signal; arranging coefficients into a number of subband groups corresponding to different frequency bands of the LFE channel signal; quantizing coefficients in each secondary frequency band group according to a frequency response curve of the low-pass filter; encoding the quantized coefficients in each subband group using an entropy decoder that is tuned for the subband groups; and generating a bitstream comprising the encoded quantized coefficients; and storing the bitstream on a storage device or streaming the bitstream to a downstream device.

The invention discloses a non-uniform quantization method and device based on density sensing clustering, equipment and a storage medium, and relates to the technical field of network communication, and the method comprises the steps: obtaining a tap coefficient of an equalizer; performing clustering division on the tap coefficient according to a preset quantization bit width to obtain a plurality of target clusters; determining a quantization parameter corresponding to the target cluster according to the dynamic range of the intra-cluster coefficient in the target cluster, wherein the quantization parameter comprises a scaling factor and a zero offset parameter; and independently and uniformly quantizing the tap coefficient in the target cluster according to the quantization parameter to obtain a recovery coefficient. According to the invention, the coefficient is adaptively divided into a plurality of clusters based on density sensing clustering, and uniform quantization is independently performed on each cluster, so that high-precision quantization of the equalizer coefficient under extremely low bits is completed, and the storage efficiency of coefficient quantization and the performance of the equalizer are improved.

The invention relates to a low latency low frequency effect codec. In some embodiments, a method of encoding a low frequency effect (LFE) channel includes receiving a time domain LFE channel signal; filtering the time domain LFE sound channel signal by using a low-pass filter; converting the filtered time domain LFE channel signal into a frequency domain representation of the LFE channel signal comprising a number of coefficients representing a spectrum of the LFE channel signal; arranging coefficients into a number of subband groups corresponding to different frequency bands of the LFE channel signal; quantizing coefficients in each secondary frequency band group according to a frequency response curve of the low-pass filter; encoding the quantized coefficients in each subband group using an entropy decoder that is tuned for the subband groups; and generating a bitstream comprising the encoded quantized coefficients; and storing the bitstream on a storage device or streaming the bitstream to a downstream device.

The application discloses a kind of stability detection method, device, equipment and medium of multi-conversion station system, it is related to power system technical field, method includes: obtaining the impedance matrix of multi-conversion station system;Obtain the port admittance matrix of converter in multi-conversion station system;According to impedance matrix and port admittance matrix, construct the return difference matrix of multi-conversion station system;Generalized radius coefficient of return difference matrix is defined;If generalized radius coefficient is less than preset threshold in research frequency band, then stability criterion is simplified based on generalized diagonal dominance, whether multi-conversion station system is stable according to the stability criterion after simplification is detected.The application constructs the return difference matrix of multi-conversion station system, and the coupling relationship between converter is quantified according to generalized radius coefficient of return difference matrix, if generalized radius coefficient is less than preset threshold, then it can be determined as weak coupling relationship, and then stability criterion is simplified based on generalized diagonal dominance, can reduce the complexity of detecting the stability of multi-conversion station system and improve detection efficiency.

The invention relates to a low latency low frequency effect codec. In some embodiments, a method of encoding a low frequency effect (LFE) channel includes receiving a time domain LFE channel signal; filtering the time domain LFE sound channel signal by using a low-pass filter; converting the filtered time domain LFE channel signal into a frequency domain representation of the LFE channel signal comprising a number of coefficients representing a spectrum of the LFE channel signal; arranging coefficients into a number of subband groups corresponding to different frequency bands of the LFE channel signal; quantizing coefficients in each secondary frequency band group according to a frequency response curve of the low-pass filter; encoding the quantized coefficients in each subband group using an entropy decoder that is tuned for the subband groups; and generating a bitstream comprising the encoded quantized coefficients; and storing the bitstream on a storage device or streaming the bitstream to a downstream device.

Systems, methods, and devices for wireless communication are described. A method of wireless communication includes receiving, by a wireless device, configuration signaling. The method also includes determining, by the wireless device, a precoding matrix indicator (PMI), where the PMI is based on a codebook indicated by the configuration signaling and the PMI corresponds to a precoding matrix applicable to more than 32 antenna ports of a network device. The method also includes transmitting, by the wireless device, the PMI. In some embodiments, the method includes configuration of oversampling factors, configuration of codebook subset restriction, selection of a spatial domain (SD) / frequency domain (FD) basis, non-zero coefficient indication, and non-zero coefficient quantization.

The invention provides a ship sensing data optimization method and device, and the method comprises the steps: determining a correlation calculation coefficient of each parameter sensor based on the distribution characteristics of to-be-optimized ship data of each parameter sensor, and then decomposing the to-be-optimized ship data based on a variational mode decomposition algorithm, the correlation between the ship data to be optimized and a plurality of intrinsic mode functions is quantitatively evaluated based on correlation calculation coefficients corresponding to the parameter sensors, and finally partition optimization reconstruction is performed based on the correlation, so that multi-source ship data optimization which automatically adapts to data features and dynamically processes real-time data is realized. The method effectively overcomes the dependence of a traditional method on artificial experience, can carry out efficient and accurate denoising processing on sensor data of a marine nuclear power system under a complex background, remarkably improves the data quality, provides more reliable data input for subsequent ship state analysis, evaluation and control decision, and improves the reliability of data processing. Therefore, safe and stable operation of the nuclear power system is guaranteed.

The invention relates to a low latency low frequency effect codec. In some embodiments, a method of encoding a low frequency effect (LFE) channel includes receiving a time domain LFE channel signal; filtering the time domain LFE sound channel signal by using a low-pass filter; converting the filtered time domain LFE channel signal into a frequency domain representation of the LFE channel signal comprising a number of coefficients representing a spectrum of the LFE channel signal; arranging coefficients into a number of subband groups corresponding to different frequency bands of the LFE channel signal; quantizing coefficients in each secondary frequency band group according to a frequency response curve of the low-pass filter; encoding the quantized coefficients in each subband group using an entropy decoder that is tuned for the subband groups; and generating a bitstream comprising the encoded quantized coefficients; and storing the bitstream on a storage device or streaming the bitstream to a downstream device.

Methods and apparatus for image compression / decompression using tensor product B-spline (TPB) representations. According to an example embodiment, an image-compression method includes generating a plurality of TPB models representing an image, including a TPB model for approximating a spatial reshaping function and a plurality of patch-wise TPB models for estimating the image signal. In some examples, the plurality of patch-wise TPB models includes a plurality of luma-channel TPB models and a plurality of chroma-channel TPB models. The spatial reshaping function is configured to shift a non-uniform distribution of local content complexity in the image toward being more uniform. The method also includes generating a metadata stream carrying metadata representing sets of coefficients of various TPB models. At least a portion of the metadata is generated by quantizing the corresponding coefficients to a smaller number of bits and applying arithmetic coding to the quantized coefficients.

This invention provides a method and system for joint probabilistic prediction of three earthquake elements associated with TLF-GV signals, belonging to the field of earthquake prediction technology. It aims to solve the problems of traditional three-element prediction lacking joint fusion, difficulty in handling evidence conflicts, and fixed weights. The method includes: extracting the physical characteristics of the TLF-GV signal, taking the prediction results of the previous three elements and model confidence parameters, concatenating them into a feature vector, inputting it into a dynamic weighted prediction model constructed by a shallow MLP, and outputting time, magnitude, and location weights; dividing the three elements into 3×3×3=27 "time-magnitude-location" propositions, generating a basic probability assignment (BPA) for each proposition based on the weights, and quantifying evidence contradictions through a conflict coefficient K; obtaining the joint BPA using the Dempster combination rule, calculating the mean of the confidence function and likelihood function of each proposition as the comprehensive probability, and extracting the proposition with the highest probability as the coupling result. This method significantly improves the scientific rigor and practicality of short-term strong earthquake prediction.

The invention relates to a low latency low frequency effect codec. In some embodiments, a method of encoding a low frequency effect (LFE) channel includes receiving a time domain LFE channel signal; filtering the time domain LFE sound channel signal by using a low-pass filter; converting the filtered time domain LFE channel signal into a frequency domain representation of the LFE channel signal comprising a number of coefficients representing a spectrum of the LFE channel signal; arranging coefficients into a number of subband groups corresponding to different frequency bands of the LFE channel signal; quantizing coefficients in each secondary frequency band group according to a frequency response curve of the low-pass filter; encoding the quantized coefficients in each subband group using an entropy decoder that is tuned for the subband groups; and generating a bitstream comprising the encoded quantized coefficients; and storing the bitstream on a storage device or streaming the bitstream to a downstream device.

The invention relates to a low latency low frequency effect codec. In some embodiments, a method of encoding a low frequency effect (LFE) channel includes receiving a time domain LFE channel signal; filtering the time domain LFE sound channel signal by using a low-pass filter; converting the filtered time domain LFE channel signal into a frequency domain representation of the LFE channel signal comprising a number of coefficients representing a spectrum of the LFE channel signal; arranging coefficients into a number of subband groups corresponding to different frequency bands of the LFE channel signal; quantizing coefficients in each secondary frequency band group according to a frequency response curve of the low-pass filter; encoding the quantized coefficients in each subband group using an entropy decoder that is tuned for the subband groups; and generating a bitstream comprising the encoded quantized coefficients; and storing the bitstream on a storage device or streaming the bitstream to a downstream device.

The present disclosure relates to low-latency low-frequency effect codecs. In some embodiments, a method of encoding a low-frequency effect (LFE) channel includes receiving a time-domain LFE channel signal, filtering the time-domain LFE channel signal using a low-pass filter, converting the filtered time-domain LFE channel signal to a frequency-domain representation of the LFE channel signal including a number of coefficients representing a spectrum of the LFE channel signal, arranging coefficients into a number of sub-band groups corresponding to different frequency bands of the LFE channel signal, quantizing coefficients in each sub-band group according to a frequency response curve of the low-pass filter, encoding the quantized coefficients in each sub-band group using an entropy coder tuned for the sub-band group, and generating a bitstream including the encoded quantized coefficients, and storing the bitstream on a storage device or streaming the bitstream to a downstream device.

Methods and apparatus for image compression / decompression using tensor product B-spline (TPB) representations. According to an example embodiment, an image-compression method includes generating a plurality of TPB models representing an image, including a TPB model for approximating a spatial reshaping function and a plurality of patch-wise TPB models for estimating the image signal. In some examples, the plurality of patch-wise TPB models includes a plurality of luma-channel TPB models and a plurality of chroma-channel TPB models. The spatial reshaping function is configured to shift a non-uniform distribution of local content complexity in the image toward being more uniform. The method also includes generating a metadata stream carrying metadata representing sets of coefficients of various TPB models. At least a portion of the metadata is generated by quantizing the corresponding coefficients to a smaller number of bits and applying arithmetic coding to the quantized coefficients.

The application relates to a voltage-current oversampling and dynamic interpolation method, device and storage medium, wherein during output, a target voltage is used to calculate a DAC digital quantity, the DAC digital quantity is decomposed into an integer reference value and a decimal part, a decimal error is converted into a time domain adjustment parameter through coefficient quantization, and finally in a continuous output period, two adjacent levels are alternately output by the DAC according to the parameter, the output time proportion is accurately controlled, and the average voltage is forced to approach a set value. During back reading, voltage and current signals are synchronously collected in a fixed high-frequency period, high-signal-to-noise ratio intermediate data units are formed through real-time accumulation, a dynamic circular buffer is used to adaptively average a plurality of units, a high-precision conversion value is output, and the dynamic circular buffer is quickly reset when data suddenly changes. The application cooperates a common-precision ADC and a DAC through a pure software algorithm, effectively breaks through the limitation of inherent resolution of hardware, and improves the system measurement precision and output accuracy without increasing the hardware cost.

A method and apparatus for image compression / decompression using a tensor product B-spline (TPB) representation. According to one example embodiment, the image compression method includes generating a plurality of TPB models representing an image, including a TPB model for approximating a spatial reshaping function and a plurality of patch-wise TPB models for estimating an image signal. In some examples, the plurality of patch-wise TPB models include a plurality of luma channel TPB models and a plurality of chroma channel TPB models. The spatial reshaping function is configured to shift a non-uniform distribution of local content complexity within the image to a more uniform distribution. The method also includes generating a metadata stream carrying metadata representing sets of coefficients of the various TPB models. At least a portion of the metadata is generated by quantizing corresponding coefficients to a fewer number of bits and applying arithmetic coding to the quantized coefficients.

The invention relates to a low latency low frequency effect codec. In some embodiments, a method of encoding a low frequency effect (LFE) channel includes receiving a time domain LFE channel signal; filtering the time domain LFE sound channel signal by using a low-pass filter; converting the filtered time domain LFE channel signal into a frequency domain representation of the LFE channel signal comprising a number of coefficients representing a spectrum of the LFE channel signal; arranging coefficients into a number of subband groups corresponding to different frequency bands of the LFE channel signal; quantizing coefficients in each secondary frequency band group according to a frequency response curve of the low-pass filter; encoding the quantized coefficients in each subband group using an entropy decoder that is tuned for the subband groups; and generating a bitstream comprising the encoded quantized coefficients; and storing the bitstream on a storage device or streaming the bitstream to a downstream device.

The invention discloses an image classification method based on sparse and quantization of an addition neural network, and the method comprises the steps: carrying out the sparse and quantization of the addition neural network, constructing an image classification prediction network model, carrying out the lossless truncation of a weight in the network to a distribution range which is the same as an input image, carrying out the calculation of a truncation value in advance, and enabling the truncation value to serve as a bias term, therefore, the sparseness of the weight is increased; secondly, mixing precision sharing coefficient quantification is carried out on the sparse addition neural network, grouping is carried out along a weight input channel, scaling factors of the weight are selected, and input and the weight are quantified at the same time; and calculating input image data through the image classification prediction network model, extracting feature information of a computer image, and outputting an image classification result. The method can reduce the reasoning energy and hardware overhead of the image classification prediction network model, and improves the efficiency and precision of image classification and recognition.

The invention relates to the technical field of power system control, in particular to a physical guidance primary frequency modulation adaptive control method and system, and the method comprises the steps: constructing a linearized offshore wind power system transfer function model; determining a dominant pole and carrying out characteristic root analysis on the dominant pole; introducing a modal response regulation and control coefficient, and quantifying the regulation and control capability of the control parameters on the dominant modal of the system so as to determine the differentiated adjustment step length proportion of the control parameters; defining an energy function describing the system frequency deviation, and analyzing the derivative of the energy function to represent the evolution direction of the system state; constructing a reinforcement learning agent based on a double-delay depth deterministic strategy gradient TD3 algorithm; applying the modal response regulation and control equilibrium principle to the action space design of the intelligent agent, and fusing the derivative information of the energy function into the reward function design; and the trained reinforcement learning agent is utilized to adaptively adjust the control parameters of the network construction type energy storage according to the real-time state of the system so as to complete the adaptive optimization of the primary frequency modulation.

In some implementations, a method of encoding a low frequency effect (LFE) channel includes receiving a time domain LFE channel signal, filtering the time domain LFE channel signal using a low pass filter, converting the filtered time domain LFE channel signal to a frequency domain representation of the LFE channel signal including a number of coefficients representing a spectrum of the LFE channel signal, arranging coefficients into a number of sub-band groups corresponding to different frequency bands of the LFE channel signal, quantizing coefficients in each sub-band group according to a frequency response curve of the low pass filter, encoding the quantized coefficients in each sub-band group using an entropy coder tuned for the sub-band group, and generating a bitstream including the encoded quantized coefficients, and storing the bitstream on a storage device or streaming the bitstream to a downstream device.

The invention relates to a low latency low frequency effect codec. In some embodiments, a method of encoding a low frequency effect (LFE) channel includes receiving a time domain LFE channel signal; filtering the time domain LFE sound channel signal by using a low-pass filter; converting the filtered time domain LFE channel signal into a frequency domain representation of the LFE channel signal comprising a number of coefficients representing a spectrum of the LFE channel signal; arranging coefficients into a number of subband groups corresponding to different frequency bands of the LFE channel signal; quantizing coefficients in each secondary frequency band group according to a frequency response curve of the low-pass filter; encoding the quantized coefficients in each subband group using an entropy decoder that is tuned for the subband groups; and generating a bitstream comprising the encoded quantized coefficients; and storing the bitstream on a storage device or streaming the bitstream to a downstream device.