434 results about "Channel correlation" patented technology

The invention relates to the technical field of weighing equipment detection, and discloses a detection output method, device and equipment for weighing equipment and a storage medium, and the method comprises the steps: carrying out the preprocessing and analog-to-digital conversion of original output signals of a plurality of weighing sensors in the weighing equipment, and obtaining synchronous digital signal data; bayesian multi-channel signal fusion and anomaly detection are carried out based on the synchronous digital signal data, and multi-channel fusion signal data and an anomaly detection identifier are obtained; performing inter-channel correlation analysis and adaptive weight distribution according to the abnormal detection identifier and the multi-channel fusion signal data to obtain a multi-channel weighted fusion result and a calibration compensation parameter; and carrying out real-time fault isolation and multi-channel working state identification on the multi-channel weighted fusion result based on the calibration compensation parameter, and generating a weighing detection result, the weight distribution can be automatically optimized according to the real-time working state and the signal quality of each weighing sensor channel, and the accuracy and the stability of the measurement of the weighing equipment are improved.

Systems, methods, and instrumentalities are described herein that may be associated with frame-based equipment (FBE) channel access in sidelink (SL) unlicensed. A wireless transmit / receive unit (WTRU) may receive configuration information that indicates a channel busy ratio (CBR) threshold. The WTRU may determine a CBR value associated with a channel in a listen before talk (LBT) band. The WTRU may compare the CBR value to the CBR threshold. The WTRU may determine a channel access parameter based on the comparison of the CBR value to the CBR threshold. The WTRU may change the channel access parameter.

The invention provides a motion intention recognition control method and system based on electroencephalogram signals, and relates to the technical field of motion intention recognition. According to the method, multi-channel electroencephalogram and peripheral physiological or motion data are collected, alignment, preprocessing and frequency band division are carried out, and space-frequency-time joint representation is constructed in combination with cross-channel association and time sequence statistics; the motion intention state probability, intensity and confidence coefficient are output through a graph time sequence decoder, and self-adaption is achieved based on feature distribution alignment; incremental updating is executed under confidence driving, and error learning is avoided in combination with an error correction mechanism; asynchronous judgment is realized through double-threshold hysteresis gating, and stable switching from unintentional state to intentional state is ensured; and finally mapping the motion intention and the intensity into a control instruction of an exoskeleton or a functional electrical stimulator under safety supervision. According to the method, a complete closed-loop link from electroencephalogram signal input to execution mechanism output is formed, and recognition precision, robustness, adaptability and safety are considered.

An apparatus may include a receiver configured to receive a reference signal using a channel, a transmitter configured to transmit a representation relating to the channel, and a processing circuit configured to determine channel information based on the reference signal, generate, using a model, the representation based on the channel information, and transfer, using the receiver or the transmitter, model information to specify the model. The model information may include an identifier for the model. The model information may include structure information for the model. The model information may include information about a type of input for the model. The model information may include information about a format of input for the model. The model information may include mapping information for mapping channel information to an input of the model. The mapping information may include information for a first subband, and information for a second subband.

The invention discloses a disturbance of consciousness electroencephalogram discrimination method and system adaptive to channel deletion. According to the method, on the basis of an electroencephalogram classification model of a deep network, automatic discrimination of disturbance of consciousness (MCS and UWS) is carried out with high accuracy according to resting-state electroencephalogram energy of a patient. The model utilizes a time domain double-branch CNN module and a space-time Transform module to learn features in electroencephalogram data hierarchically; and a model architecture with variable channel dimensions is introduced, an inter-channel association learning method fusing electrode position information and a training strategy of channel random discarding are introduced, so that the model can adapt to a scene in which part of channels are missing, and the clinical applicability of the method is improved.

The invention discloses an image fusion method based on multi-dimensional complementary features and multi-scale detail enhancement, and the method comprises the steps: calculating an edge image of a source image, and splicing the edge image with the source image in a channel dimension; enhancing feature textures and edge details by a high-frequency detail enhancement module; generating three feature maps with different scales step by step through continuous down-sampling operation; from the deepest scale, the infrared and visible light features of the hierarchy are fused through a parallel three-branch fusion module; the fused features are used for reconstructing a low-resolution fusion result, and the low-resolution fusion result is transmitted to an upper layer through up-sampling operation; and in the scale of the upper layer, the steps are repeated until a final full-resolution fusion image is generated. A parallel multi-dimensional complementary fusion network PMCFusion is set, cooperative perception and efficient integration of spatial features, channel correlation and frequency domain information are achieved through a parallel three-branch fusion module PTFM, and through cross-dimensional attention interaction, the PMCFusion can selectively enhance multi-dimensional features and achieve deep complementation.

The invention discloses a photovoltaic power generation time sequence prediction method based on periodic modeling and channel interaction, and the method comprises the steps: collecting and processing the historical data of photovoltaic power generation; then, extracting a learnable periodic mode in the time sequence, and removing a periodic component to obtain a residual component; then, through reversible instance normalization, sequence embedding, a channel interaction module and a linear predictor, modeling and prediction of a residual component are completed; and finally, adding the predicted residual component and the periodic component to generate a final prediction result. Through an aggregated channel interaction strategy, the calculation complexity is reduced while the channel correlation is captured, the dependence on an abnormal channel is reduced, and the robustness and the expansion capability of the model are improved; meanwhile, by directly modeling a periodic mode in the time sequence, the capability of extracting inherent periodicity in the photovoltaic power generation time sequence data is improved, so that future power generation data is predicted more accurately; the method can be widely applied to optimal scheduling and management of a photovoltaic power generation system.

The invention discloses a cable partial discharge signal noise separation mode identification method and system, and particularly relates to the technical field of cable partial discharge detection, in a multi-cable stacking environment, partial discharge signals are synchronously collected through multiple types of sensors such as a high-frequency current sensor, an ultrasonic sensor and an electromagnetic antenna; performing band-pass filtering, wavelet denoising and multi-channel synchronous alignment on the acquired signals to suppress background noise and retain key features of partial discharge pulses; separating the mixed signals by adopting independent component analysis; calculating a decision coefficient based on an inter-channel correlation coefficient, a signal-noise power ratio and an amplitude dynamic range, and judging whether to introduce a denoising method based on deep learning; for the waveform after noise separation, executing an amplitude re-calibration process so as to correct amplitude scaling uncertainty, and extracting multi-dimensional time domain, frequency domain and phase features; and a support vector machine and other machine learning algorithms are combined to realize automatic identification of partial discharge types.

This disclosure provides methods, components, devices and systems for dynamic bandwidth expansion. Some aspects more specifically relate to one or more configuration- or signaling-based mechanisms according to which various wireless communication devices, such as access points (APs) or stations (STAs), may communicate via an expanded bandwidth. For example, a total available bandwidth may be divided into different wireless channels, with each wireless channel being associated with a respective basic service set (BSS) of a respective AP. A wireless communication device may establish a communication link associated with a first wireless channel (the first wireless channel being associated with a BSS bandwidth of the wireless communication device) and, in accordance with one or more criteria, may communicate via a bandwidth that includes the first wireless channel associated with the BSS bandwidth and one or more other wireless channels outside of the BSS bandwidth.

The invention provides a channel state information feedback enhancement method and system based on bidirectional channel correlation, and the method is executed at a base station end, and comprises the steps: receiving a downlink channel state information semantic vector which is coded, compressed and quantized by a user end through a deep joint source channel; carrying out inverse quantization on the semantic vector to obtain an intermediate semantic vector; based on the intermediate semantic vector, retrieving a related historical uplink semantic vector from an uplink channel semantic knowledge base; performing fusion enhancement on the intermediate semantic vector and the retrieval result through an attention mechanism to generate an enhanced semantic vector; inputting the enhanced semantic vector into a decoder, and outputting a reconstructed downlink channel state information matrix; wherein the encoder, the enhancement module and the decoder perform end-to-end joint training optimization by minimizing a reconstruction error. According to the method, the semantics is enhanced at the receiving end by utilizing the correlation of the uplink and downlink channels, the feedback precision and the system robustness are remarkably improved, and the method is suitable for a frequency division duplex system.

A wireless transmit / receive unit (WTRU) comprises a processor configured to receive a configuration of channel correlation measurements from a network. The configuration may be associated with an aggregation group. The processor may detect a trigger to perform the channel correlation measurements, determine one or more WTRUs associated with the aggregation group to perform the channel correlation measurements, send a request to perform the channel correlation measurements to each WTRU of the one or more WTRUs associated with the aggregation group, receive a response from at least one WTRU of the one or more WTRUs associated with the aggregation group, determine a correlation of the channel correlation measurements performed by the one or more WTRUs in the aggregation group, and send a reporting message to the network or the at least one WTRU of the one or more WTRUs.

Embodiments of the present disclosure relate to devices, methods, and computer-readable media for transmit cancellation. According to an embodiment of the present disclosure, a terminal device receives a UL cancel indication from a network device. The terminal device receives, from a network device, a resource indicator associated with an uplink channel. Then, based on the time unit of the uplink channel being an SBFD time unit, the terminal device transmits the uplink channel using a first resource indicated in a first resource set by the resource indicator. The SBFD time unit is configured with frequency sub-bands for different link directions. Based on the time unit being a non-SBFD time unit, the terminal device transmits the uplink channel using a second resource indicated in a second resource set by the resource indicator. In this manner, the SRS configuration may be adapted to or coordinated with an SBFD mechanism.

The invention relates to the technical field of electromagnetic shielding testing devices, and discloses a testing device for an electromagnetic shielding material. The device comprises a signal transmitting module, a signal receiving module, a parameter calibration module and a shielding effectiveness calculation module. The signal transmitting module outputs electromagnetic signals with different frequencies from a plurality of signal sources, and a to-be-tested signal set is formed after preprocessing and amplitude adjustment; the signal receiving module collects residual signals penetrating through the shielding material and converts the residual signals into analyzable signals; the parameter calibration module extracts signal parameters to construct an electromagnetic signal parameter matrix, and constructs a transmission correlation graph through the channel correlation graph and the key signal parameter correlation degree; and the shielding effectiveness calculation module calculates a shielding effectiveness core parameter sequence in combination with the signal channel entropy and the correlation graph, and finally inputs the shielding effectiveness core parameter sequence into an effectiveness detection model of the convolutional neural network model to generate a test report. The device can comprehensively process multi-frequency signals, deeply analyze signal parameter correlation and accurately calculate the shielding effectiveness, and is suitable for electromagnetic shielding material performance testing.

The invention discloses a near-field channel state information feedback method under a super-large scale array based on Transform, which comprises the following steps: in a downlink XL-MIMO system in a near-field area, a user side performs two-dimensional matrix processing on acquired CSI data and transmits the processed CSI data to a coding end; two-channel coding compression is carried out on the CSI matrix, a first channel uses an encoder to extract channel related characteristics, and a second channel enables an original CSI matrix to pass through a linear network so as to reserve original information; compressing the output of the two channels, and splicing to generate a low-dimensional code word to be fed back; the base station side decoding end splits the low-dimensional code word and decompresses the low-dimensional code word of the corresponding channel; decompressed dual-channel code words are respectively input to two ends of a decoder; and carrying out size change on the output of the decoder to obtain the estimated original CSI. According to the method, angle and distance information of a near-field channel is fully utilized, and efficient CSI compression and high-precision reconstruction are realized.

Systems, apparatuses, methods, and computer-readable media are provided for power control aspects for message A (MsgA) physical uplink shared channel (PUSCH). The approach includes determining a transmission power for a PUSCH associated with a physical random access channel (PRACH) in a 2-step random access channel (RACH) mode, where the transmission power for the PUSCH is determined based on a transmission power of the associated PRACH and a power offset. The approach further includes ramping up a transmission power of the PRACH and PUSCH until a maximum transmission power is reached.

The embodiment of the invention provides a communication method, a related device, a storage medium and a program product, and is applied to the technical field of communication. The communication method comprises the following steps that: a first system base station receives a second system frequency band channel parameter from a second system base station, and calculates a cross-frequency band channel measurement auxiliary parameter by using the second system frequency band channel parameter; and sending the cross-band channel measurement auxiliary parameter to the user equipment, receiving an uplink pilot signal sent by the user equipment referring to the cross-band channel measurement auxiliary parameter, and performing channel estimation by using the uplink pilot signal and the cross-band channel measurement auxiliary parameter to obtain a first system frequency band channel parameter. According to the scheme provided by the embodiment of the invention, the cross-band channel measurement auxiliary parameter is obtained by using the second system frequency band channel parameter based on the channel correlation between the frequency bands used by different systems, so that the first system base station is assisted to reduce the related overhead of channel measurement, and the capacity and experience of the first system system are improved.

Apparatuses and methods are disclosed for pre-emption priority level for Uplink Control Information (UCI) and / or Physical Uplink Shared Channel (PUSCH) conflict resolution. In one embodiment, a method implemented in a network node includes indicating to a wireless device (WD) a priority associated with at least one uplink (UL) channel; and receiving at least one UL signal based at least in part on the indicated priority. In another embodiment, a method implemented in a WD includes determining a priority associated with at least one of at least two uplink (UL) channels; and resolving a conflict between the at least two uplink channels based at least in part on the determined priority.

The embodiment of the invention provides a communication method and a related device. The method comprises the following steps: sending first information indicating a first group of reference channels related to a first environment parameter set to user equipment; and sending second information related to the first environment parameter set to the user equipment, wherein the second information is used for determining one or more reference channels from the first group of reference channels. In the application, a central device can inform a user equipment of which environment parameter set is related by sending the second information, and help the user equipment determine at least one reference channel from a group of reference channels related to the environment parameter set indicated by the second information. According to the technical scheme, the validity of the reference channel which comes from the user equipment and is influenced by the environment parameter set can be ensured. Furthermore, the central device can determine the information related to the first DL channel without sending the channel measurement of the first DL channel, which can solve the problem of large signaling overhead caused by sending the channel measurement.

Embodiments of the present disclosure relate to a beamforming solution for FDD MIMO communication. A first device receives a reference signal from a second device in a first channel, and determines a covariance matrix associated with the first channel. The first device determines a set of beamforming vectors from the covariance matrix based on the number of dominant angles of arrival associated with the reference signal and the number of beams associated with the set of beamforming vectors, and performs a transmission to the second device based on the set of beamforming vectors in a second channel. In this way, beamforming vectors can be calculated from the transformed channel covariance matrix with the angular spread and imperfect reciprocity considered.

The application relates to the technical field of electromagnetic shielding test devices, and discloses a test device for electromagnetic shielding materials. The device comprises a signal emission module, a signal receiving module, a parameter calibration module and a shielding effectiveness calculation module. The signal emission module outputs electromagnetic signals of different frequencies from multiple signal sources, and forms a set of to-be-tested signals after pre-processing and amplitude adjustment; the signal receiving module collects residual signals passing through the shielding material and converts the residual signals into analyzable signals; the parameter calibration module extracts signal parameters to construct an electromagnetic signal parameter matrix, constructs a transmission correlation atlas through a channel correlation graph and a key signal parameter correlation degree; the shielding effectiveness calculation module combines signal channel entropy and the correlation atlas to calculate a shielding effectiveness core parameter sequence, and finally inputs the effectiveness detection model of a convolutional neural network model to generate a test report. The device can comprehensively process multiple-frequency signals, deeply analyze signal parameter correlation, accurately calculate shielding effectiveness, and is suitable for electromagnetic shielding material performance testing.

In end-to-end compression, a deep neural-network based encoder can be used to encode an image. The embeddings output from the encoder are quantized and encoded with a lossless encoder. Advantageously, at least one embodiment allows improving the latent entropy coding by further reducing the redundancies in the quantized latent. To that end, at least one embodiment discloses taking into account channels importance by coding an indication of a channel activity (or significance): performing post-conditional entropy coding by computing conditional probability based on a context afterwards: using channels reordering to improve inter channel correlation: or performing RDOQ like process by optimizing the main latent for a particular image.

The invention discloses a gearbox fault diagnosis method based on multi-channel feature fusion. The gearbox fault diagnosis method comprises the steps that vibration signals of a gearbox to be diagnosed are collected through sensors installed at different positions in a multi-channel mode; for each vibration signal, obtaining a two-dimensional time-frequency image of the vibration signal by using a sliding window function, and respectively extracting features of the vibration signal and the two-dimensional time-frequency image by using a multi-layer gated convolutional network to obtain a one-dimensional feature and a two-dimensional feature of the vibration signal; fusing the one-dimensional features and the two-dimensional features of the vibration signals collected by the channels by using a convolution attention module to obtain fusion features of the gearbox to be diagnosed; and based on the fusion features of the to-be-diagnosed gearbox, performing fault diagnosis on the to-be-diagnosed gearbox by using a gearbox fault diagnosis model. According to the method, the comprehensiveness of feature expression is improved, and the channel correlation and the spatial correlation of the features are better captured, so that the modeling capability of the model for complex features is improved.

The invention relates to the technical field of computer vision, in particular to an improved YOLOv8n lightweight inland ship detection algorithm. According to the technical scheme, the method comprises the steps of designing a lightweight detection head EFSDH and replacing an original decoupling detection head, introducing a neck network lightweight method slip-check, designing a global channel adaptive amplitude pruning algorithm GCAMBP for channel pruning, and designing a space-channel correlation knowledge distillation method SCCKD for knowledge distillation. According to the light-weight YOLO model for inland ship detection, the detection performance of the model is successfully improved, meanwhile, light weight is achieved, and the problems of real-time performance and accuracy in a computing resource limited environment are solved.

A channel-associated information transfer method and apparatus, and a device are related to the field of storage technologies and provide a transfer mechanism applied to channel-associated information of data of a universal flash storage (UFS). The method includes a UFS device sending a first ready-to-transfer (RTT) frame to a host, where the first RTT frame indicates to transfer first target data. The first RTT frame includes channel-associated control information. The channel-associated control information is used to control transfer of first channel-associated information of the first target data. When the host receives the first RTT frame, the host sends a first data frame to the UFS device, where the first data frame includes the first target data and the first channel-associated information. The UFS device receives the first data frame.

Devices, systems, methods, and processes for channel selection in wireless networks for narrowband-assisted ultra-wideband (NBA-UWB) signaling and ranging. Narrowband signal overlaps the existing ISM bands and thus has high likelihood of interfering with Wi-Fi, Bluetooth Low Energy (BLE), and other technologies used inside a network device. Therefore, selection of an appropriate target channel that may be used for UWB signaling can mitigate interference with Wi-Fi / BLE signals. A network device may receive one or more channel status messages from a plurality of neighboring network devices. The channel status messages may indicate a channel associated with a respective neighboring network device and a channel metric associated with the channel. The channel metric may indicate channel quality, traffic status, signal strength, etc. Based on a set of available channels indicated by the one or more channel status messages, the network device may select a target channel to execute a UWB signaling.

Provided are a method performed by a first device and a device supporting same in a wireless communication system. The method performed by a first device in a wireless communication system comprises the steps of: acquiring configuration information related to a physical sidelink feedback channel (PSFCH); transmitting a first sidelink control indicator (SCI) for scheduling a physical sidelink shared channel (PSSCH) and a second SCI to a second device through a physical sidelink control channel (PSCCH); transmitting data and the second SCI including information indicating a hybrid automatic repeat and request (HARQ) feedback enabled mode to the second device through the PSSCH; and determining a PSFDCH resource related to the PSSCH on the basis of the configuration information.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive, from a network node, an indication of a slot to be associated with precoder estimation, the indication of the slot including an indication of a first precoder and one or more parameters associated with the slot. The UE may receive, from the network node and during the slot, a first one or more reference signals associated with estimating a physical channel using the first precoder and a second one or more reference signals associated with estimating a second precoder using the estimated physical channel. The UE may receive, from the network node, one or more signals based on the second precoder. Numerous other aspects are described.

The invention discloses a large-scale SIMO system optimization method, and the method comprises the steps: S1, carrying out the zero-forcing ZF preprocessing of a received signal at a receiving end, so as to eliminate the channel correlation; s2, detecting the received signal subjected to zero forcing ZF preprocessing by adopting a fast asymptotic ML detector; s3, deducing a paired error probability PEP between adjacent constellation points corresponding to the fast asymptotic ML detector; and S4, performing optimization design on the PAM constellation based on the minimum PEP so that the constellation structure can be dynamically adjusted along with system parameters. Aiming at the problem of difficulty in performance analysis and optimization caused by complex energy distribution of received signals under a channel correlation condition, the method is obviously superior to a traditional fixed equidistant constellation scheme, and a simulation result shows that the scheme provided by the invention can enable an SIMO system to be more reliable and better in performance under a correlation Rayleigh fading channel.

The embodiment of the invention provides a communication method and a related device. The method comprises the following steps: sending first information indicating a first group of reference channels to first user equipment; and receiving, from the first user equipment, second information indicating at least one first reference channel in the first group of reference channels, a distance between any one of the at least one first reference channel and a first DL channel of the first user equipment being less than or equal to a first threshold. In the application, the central device can determine the information related to the first DL channel without sending the channel measurement of the first DL channel, which can solve the problem of large signaling overhead caused by sending the channel measurement.

The invention provides a double-branch spectrum quantitative analysis method Mark-GLNet based on Pearson feature marking, and global dependency modeling and local feature extraction are collaboratively optimized. The Mark mark layer quantifies wavelength importance by using a Pearson's correlation coefficient, eliminates redundant wavelengths, and inhibits low correlation noise. Refining feature input GLNet: global branches utilize sequence continuity and cross-space correlation, dynamic weights highlight keys, and redundancy is suppressed; and local branches compensate channel correlation through multi-scale convolution, and reinforce details. Double branches are cooperated through feature compensation, redundant interference is reduced, and prediction precision is improved. Through verification of four open-source near-infrared data sets, the model is simple in structure, low in parameter quantity and calculation complexity and excellent in generalization ability, and has high practicability and expandability.