380 results about "Signal encoding" patented technology

The invention discloses a morphological gradient region replacement method based on SAM semantic segmentation and user guidance, and relates to the technical field of computer vision and image processing, and the method comprises the steps: carrying out the semantic segmentation of a to-be-processed image through an SAM model, extracting a multi-level semantic feature, carrying out the standardization and dimension reduction, extracting a causal factor based on independent component analysis, and carrying out the user guidance. A directed causal factor association graph is generated through Granger causal relationship test, and a causal attribution probability graph is generated through reverse mapping; constructing a structured causal graph, and generating a causal mask through a graph convolutional network; encoding the original interaction signal into a guide thermodynamic diagram; constructing a diffusion equation, forming a gradual change control equation by dynamically fusing and guiding the intensity distribution of the thermodynamic diagram and an image semantic diffusion item, and iteratively solving the gradual change control equation; generating an anisotropic morphological operation kernel according to the geometric curvature characteristics of each region in the replacement mask; and fusing the optimized replacement mask with the target content based on a gradient domain optimization algorithm to generate a gradient replacement image.

The invention provides a quantum circuit optimization method, device and equipment for a ZUC algorithm subcomponent, and the method comprises the steps: encoding a signal transmitted by communication into quantum bits, and inputting the quantum bits into a ZUC algorithm structure for quantum implementation; representing a first linear subcomponent in the ZUC algorithm structure as a matrix in a binary field; after a matrix in the binary field is expressed as a block matrix, a low-dimensional matrix M in the binary field is derived from the block matrix, and quantum implementation of the M is searched by using a search algorithm designed based on a matrix decomposition principle; and according to a quantum gate parallel rule, carrying out optimized multi-layer division on the quantum of the M again, obtaining the quantum of the M, carrying out optimized layering operation, and optimizing the quantum of the first linear subcomponent. According to the method provided by the invention, the quantum circuit of the subcomponent of the ZUC algorithm is optimized, so that the resource overhead of quantum implementation of the ZUC algorithm is saved.

Systems and methods for detecting and diagnosing machine faults are discussed. An exemplary system includes at least one sensor node to sense a signal indicative of an operation status of a machine part, and a machine health analyzer circuit to generate a computational machine fault model comprising an autoencoder (AE) network and an associative module. The AE network encodes the sensed signal into signal features in a latent feature space, and decodes the signal features to produce a reconstructed signal. The associative module transforms the encoded signal features into an associative output using a dynamically updatable codebook. The machine health analyzer circuit detects a presence or absence of fault in the machine part based on reconstruction losses determined respectively from the reconstructed signal and the associative output. The detected fault can be presented to a user or to a process such as fault diagnosis or fault correction.

Techniques and solutions are described for encoding and decoding signals, such as audio data. Disclosed innovations can find particular use in speech coding applications, such as for real time communications. Using a neural network, contextual coding can be used to encode latent features for a current frame using a prediction from reconstructed latent features of past frames as a context. An extractor learns a residual-like feature based on such prediction and latent features of the current frame obtained using an encoder. The residual-like feature is then quantized. At a decoder portion of a coding framework, the quantized feature is dequantized and then combined with a prediction from prior reconstructed latent features to provide reconstructed features of a current frame, which can then be processed by a decoder to provide a reconstructed signal.

The invention provides a motor imagery-based rehabilitation evaluation method and system and a storage medium, and the method comprises the steps: obtaining electroencephalogram signal data collected by a subject during the execution of a motor imagery-based rehabilitation task, and extracting the frequency domain features of the electroencephalogram signal data; inputting the frequency domain characteristics of the electroencephalogram signal data into a pre-trained encoder for encoding, and outputting to obtain embedded representation of the electroencephalogram signal data; inputting the embedded representation of the electroencephalogram signal data into a natural language decoder, and outputting to obtain a rehabilitation evaluation result of the subject; wherein in the process of training the signal encoding module to obtain the encoder, the signal encoding module is updated through encoding loss, so that the embedding representation of the label text and the embedding representation of the corresponding electroencephalogram signal data realize cross-modal alignment. According to the method, the end-to-end generation from the original electroneurographic signal to the multi-modal evaluation information can be realized.

The invention relates to the technical field of voice semantics, can be applied to business system platforms of financial science and technology, medical health and the like, and discloses a high-fidelity music reconstruction method, device, equipment and medium, and the method comprises the steps: obtaining a to-be-processed music signal, carrying out the signal coding of the to-be-processed music signal, and obtaining a low-dimensional music signal; performing multi-scale convolution on the low-dimensional music signal to obtain a multi-scale music feature; performing multi-head self-attention calculation on the multi-scale music features to obtain attention values of the multi-scale music features; performing feature fusion on the multi-scale music features according to the attention values to obtain fused music features; performing non-autoregression decoding on the fused music features to obtain target acoustic features; and performing waveform reconstruction on the to-be-processed music signal according to the target acoustic feature to obtain a target music signal. According to the invention, the music signal reconstruction quality and reconstruction efficiency can be improved.

The invention belongs to the technical field of wireless communication and artificial intelligence, and discloses a multi-mode semantic communication method and device oriented to multiple tasks, which avoid low-layer signal coding transmission of original data through extraction and transmission of semantic features, realize end-to-end optimization and channel adaptive robust transmission of semantic level communication, and improve the communication efficiency. The bandwidth occupation is obviously reduced; and the anti-noise performance is improved. Semantic transmission and task execution of multi-source data such as images, texts and voices under a unified framework are achieved through a shared neural network encoder and a channel interface, the robustness of tasks is kept under the complex channel condition, and cross-domain semantic expression among modes such as vision, texts and voices is achieved through the framework. Radio frequency data are sent and received in a real hardware platform, physical combination of an algorithm and a radio frequency link is achieved, and implementation of deep semantic communication in an actual wireless link shows that the method has engineering deployability and expansibility.

The present invention provides a video signal encoding / decoding method and an apparatus for the method. The video decoding method of the present invention includes the following steps: determining whether to apply a merged motion difference encoding method to a current block; generating a merged candidate list for the current block; determining a merged candidate for the current block based on the merged candidate list; and deriving a motion vector for the current block based on the merged candidate.

The invention provides an equipment fault diagnosis method and device based on a large language model and electronic equipment, and the method comprises the steps: collecting a vibration signal of the equipment, and extracting the time-frequency characteristics of the vibration signal through a signal encoder; a description text corresponding to the time-frequency feature is retrieved from the description text data set; and editing the cue word template based on the description text and the time-frequency features, and inputting the cue word template into the large language model to obtain an equipment fault diagnosis result, an equipment fault diagnosis basis and an equipment fault maintenance scheme output by the large language model. By using a large language model and a retrieval enhancement generation technology, the problem of cross-working-condition fault diagnosis of equipment in a complex environment is solved, so that the accuracy of fault diagnosis is enhanced, and the generalization of diagnosis is improved.

The invention discloses a quaternary data processing system based on a multi-level signal and a dual-storage architecture, and relates to the technical field of data processing, in particular to a quaternary data processing system combining multi-level signal coding, a dual-storage architecture synchronization strategy and a quantum compatibility design. According to the system, through collaborative design of multi-level signals and a double-storage architecture, the density bottleneck and anti-interference shortages of a traditional binary system are solved, meanwhile, a classic data interface is provided for quantum calculation, and the system can be widely applied to the fields of power line communication, industrial automation, quantum calculation acceleration and the like.

A signal encoding and decoding protocol to convey discrete sets of information combined in a single carrier signal is disclosed. The protocol uses modulation of both amplitude and pulse width to carry multiple sets of information. A first signal is pulse width modulated to encode a first data and a second signal is pulse amplitude modulated to encode a second data. The two modulated signals are combined to generate a carrier signal encoded with both the first and second data.

The video decoding method of the present invention includes the following steps: determining whether to divide an encoded block into a first prediction unit and a second prediction unit; when it is determined that the encoded block is divided, determining the division type of the encoded block; deriving first motion information of the first prediction unit of the encoded block and second motion information of the second prediction unit; and obtaining prediction samples in the encoded block based on the first motion information and the second motion information.

A method of processing an amplitude modulated, AM, signal, the method comprising: receiving an AM signal comprising an encoded sequence of symbols, each symbol in the encoded sequence being from a set of predefined symbols, wherein each predefined symbol in the set of predefined symbols, when encoded, comprises an AM signal portion comprising one or more high amplitude signal periods and a low amplitude signal period, wherein the low amplitude signal period is in a different position in the AM signal portion for different predefined symbols in the set of predefined symbols; processing the received AM signal to measure an interval between two successive low amplitude signal periods in the received AM signal; based at least in part on the measured interval, identifying a symbol of the sequence of symbols encoded in the received AM signal; and performing an action based on the identified symbol.

The present disclosure relates to the technical field of communications, and provides a signal transmission method and apparatus, a storage medium and a program product, which are beneficial to reducing interference between signal transmissions. The signal transmission method comprises: sending, to a second node, configuration information of a signal to be transmitted, wherein the configuration information at least comprises an encoding configuration; if the signal to be transmitted is a first signal, the encoding configuration comprises parameters related to a first encoding mode; and if the signal to be transmitted is a second signal, the encoding configuration comprises parameters related to a second encoding mode.

A method for training a non-autoregressive TTS model includes receiving training data that includes a reference audio signal and a corresponding input text sequence. The method also includes encoding the reference audio signal into a variational embedding that disentangles the style / prosody information from the reference audio signal and encoding the input text sequence into an encoded text sequence. The method also includes predicting a phoneme duration for each phoneme in the input text sequence and determining a phoneme duration loss based on the predicted phoneme durations and a reference phoneme duration. The method also includes generating one or more predicted mel-frequency spectrogram sequences for the input text sequence and determining a final spectrogram loss based on the predicted mel-frequency spectrogram sequences and a reference mel-frequency spectrogram sequence. The method also includes training the TTS model based on the final spectrogram loss and the corresponding phoneme duration loss.

An audio communication method, an audio conversion method, a bitstream processing method, an apparatus, an electronic device, a computer-readable storage medium, and a computer program product. The audio communication method comprises: in response to a first communication request for an audio signal, acquiring, from a plurality of communication modes, a voice transformation mode for the audio signal (101); performing feature coding on the audio signal, so as to obtain a coded feature of the audio signal (102); acquiring a target timbre corresponding to the voice transformation mode, and determining a timbre feature of the target timbre (103); performing timbre conversion on the coded feature on the basis of the timbre feature, so as to obtain a target coded feature (104); and performing signal coding on the target coded feature, so as to obtain a target audio bitstream conforming to the target timbre, and transmitting the target audio bitstream to a decoding terminal (105).

An encoding method for a light signal, an electronic device, a non-transitory computer-readable storage medium, and a light signal detection circuit are provided. The encoding method for a light signal includes: detecting whether there is a change in a light intensity signal representing a light intensity, the light intensity signal being converted by a photosensitive unit from a received photon stream; encoding, in response to detecting a change in the light intensity signal, the changed light intensity signal to obtain an encoding result; and arranging the encoding result into an encoded sequence according to a time sequence relationship corresponding to changes in the light intensity, the encoded sequence representing time sequence code of the photon stream, and the time sequence relationship representing an order of the changes in the light intensity within a time period.

The invention discloses a robot grasping recognition method and system based on visual and tactile information fusion. The method comprises the following steps that S1, tactile signals are preprocessed; the method comprises the following steps: S1, integrating data acquired by each tactile sensor into a four-dimensional tensor, and constructing a basic tactile snapshot sequence; a three-level coding network composed of a CNN (Convolutional Neural Network), an LSTM (Long Short Term Memory) and a Transform Encoder is adopted to code the tactile information; S3, visual signal preprocessing and coding; s4, carrying out cross-modal alignment; and S5, large model reasoning. According to the robot grabbed object recognition method and system combining the visual features and the tactile features, the grabbed object of the robot is understood and analyzed based on the visual information and the tactile information, and the accuracy of robot actions and the completeness of tasks can be improved.

The application discloses a kind of haptic signal encoding processing method, decoding processing method and related equipment, belong to haptic codec field, the haptic signal encoding processing method of the embodiment of the application includes: obtaining at least one of the key frame sequence and first signal corresponding to each haptic signal in multiple haptic signals, the key frame sequence is obtained based on second signal, first signal is obtained based on target residual signal and third signal, target residual signal is obtained based on second signal and key frame sequence, second signal and third signal are obtained based on to haptic signal, and the frequency of second signal is less than the frequency of third signal;At least one of the following is performed: first masking processing is carried out to key frame sequence based on first masking model, and the signal after first masking processing is encoded to obtain first encoding sequence;Second masking processing is carried out to first signal based on second masking model, and the signal after second masking processing is encoded to obtain second encoding sequence.

The present disclosure relates generally to signal encoding for elements within PDF files. One implementation smooths saw-toothed edges of rasterized elements meant for encoding. Other implementations are provided too.

The present disclosure relates generally to signal encoding for value documents. One aspect of the technology relates to authentication of value documents comprising line art patterns. In one example, authentication relies of detection of signals encoded within the line art, and expected frequency domain analysis of the line art. Other combinations are described as well. For example, authentication may rely on detection of signals encoded within encoded and then printed documents, expected frequency domain characteristics encoded signals, presence or absence of halftoning, a color check and / or trained classifier analysis. Other aspects, technology, claims and combinations are described as well.

The invention belongs to the field of communication, and relates to an audio signal transmission method and related equipment, and the method comprises the steps: collecting audio signals which comprise a public network audio signal and a private network audio signal; preprocessing the public network audio signal and the private network audio signal; mixing the preprocessed public network audio signal and the preprocessed private network audio signal to obtain a mixed audio signal; encoding the mixed audio signal into a Bluetooth protocol format through an application program, and generating a Bluetooth audio signal; and transmitting the Bluetooth audio signal to a Bluetooth device. According to the application, protocol analysis and mixing processing are carried out on the private network data packet through a software level, seamless audio fusion of the public network and the private network and cooperative output of the Bluetooth are realized, the problem that audio fusion of the public network and the private network and intercommunication between the Bluetooth and the private network need additional hardware modules is solved, low-delay and high-compatibility transmission is realized, and the transmission efficiency is improved. And the user experience and the operation efficiency in a complex communication scene are improved.

The invention relates to the technical field of communication, and discloses a converged communication method for an analog signal interphone and a public network interphone, which comprises the following steps of: directly sensing the physical on-off state of a speaking right key of an analog interphone without voice signal encoding and decoding processing so as to generate a binary state signal; according to the method and the device, the state signal is mapped into a public network standardized uplink request signaling which does not bear user data, the public network standardized uplink request signaling is sent to serve as a cross-domain state beacon, and then selection scheduling of heterogeneous communication resources is triggered, so that inherent processing delay and power consumption of signal translation in an existing fusion mode are avoided, and the user experience is improved. In a content-independent lightweight beacon mode, nearly instantaneous state synchronization and efficient resource selection between heterogeneous networks are realized, and the operation reliability and adaptability of the system under complex working conditions are improved.

The invention relates to the technical field of power system equipment detection, and discloses a mouse linkage wireless intelligent triggering system and method for a switch cabinet mechanical characteristic test, and the system comprises a motion collection module which is used for collecting the operation parameters of a mouse, building an operation behavior feature library, and transmitting the operation behavior feature data to a signal coding module in real time; the signal coding module is used for receiving the operation behavior characteristic data of the mouse, collecting an opening and closing instruction electric signal generated by a telecontrol background, extracting behavior characteristics and electric signal characteristics, and generating a unique opening characteristic code and / or a closing characteristic code; the tester intelligent receiving module is used for receiving the opening feature code and / or the closing feature code, and starting a dual mechanism of time window verification and feature code matching verification to verify the feature code; and the cloud collaborative management platform is used for receiving data uploaded by the action acquisition module, the signal coding module and the tester intelligent receiving module in real time. The efficiency of testing the mechanical characteristics of the switch cabinet is improved.

The invention provides a data processing method and device, a storage medium and computer equipment, and the method comprises the steps: carrying out the traversal of to-be-processed data according to a convolution calculation rule, and encoding an initial digital domain signal corresponding to the subdata into a first optical domain signal for the current traversal subdata; inputting the first optical domain signal into an optical neural network for convolution processing and nonlinear processing to obtain a second optical domain signal of the sub-data; the convolution kernel weight used in the convolution processing is represented by using the optical constant value of the phase change material in each storage and calculation integrated unit set in the optical neural network; and converting the second optical domain signal corresponding to each subdata obtained by traversing into a target digital domain signal, and inputting the target digital domain signal into a classification neural network to obtain a classification result. The method breaks through the limitation of an existing optical neural network in the aspects of power consumption and depth, has the advantages of high efficiency, low delay, expandability and the like, and is suitable for edge intelligent calculation scenes of tasks such as image classification.

The invention discloses a multi-modal speech enhancement method and device based on a deep learning model, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining the head posture data, binaural audio signals and visual context information of a user in a virtual reality environment, coding the binaural audio signals into three-dimensional space acoustic features, and carrying out the coding of the three-dimensional space acoustic features; and extracting virtual sound source position features and lip motion features from the visual context information, inputting the features into an immersive fusion enhancement network, selectively enhancing or inhibiting acoustic features from different spatial directions, generating an enhanced audio stream, and outputting the enhanced audio stream through a binaural rendering engine. According to the method, the technical problems that in the prior art, due to the fact that multi-modal prior information cannot be effectively fused, voice enhancement lacks spatial selectivity, and an interference sound source irrelevant to vision is difficult to restrain are solved, and head posture dynamic attention and lip motion cross-modal constraint are fused; the technical effects of natural binding of auditory attention and a visual focus and effective suppression of an interference sound source are achieved.

The invention provides signal coding equipment, an imaging system and an imaging method. The signal coding equipment comprises an array waveguide grating, a coding optical fiber, a delay optical fiber and an optical splitter, the array waveguide grating is configured to convert an initial signal emitted by the light source into multiple paths of target signals; the optical splitter is configured to combine multiple paths of target signals and then emit the combined signals; a plurality of paths of coding optical fibers and a plurality of paths of delay optical fibers with different lengths are arranged behind the array waveguide grating, and each path of delay optical fiber is connected to the coding optical fiber of the corresponding coding sequence; the delay optical fiber is configured to delay a transmitted target signal, and the coding optical fiber is configured to perform pulse coding on the transmitted target signal. According to the invention, the original pulse signal is coded by using the sequence code with good orthogonality, so that the signal processing accuracy is improved. And the delay optical fibers are grouped, so that the corresponding channels in each group of channels can be simultaneously transmitted, the signal transmitting time is shortened, the signal processing efficiency is improved, and the point acquisition rate can be improved while the fuzzy distance is expanded.

The invention discloses a bearing fault classification method based on a decision tree algorithm full-analog circuit, and the method comprises the steps: enabling various bearing fault signals to pass through two layers of analog filters in sequence, and enabling the difference between the root mean square values of a low-pass output signal and a high-pass output signal of each layer of analog filter to serve as a decision condition, classifying and coding various bearing fault signals to obtain simulation signal codes; the currently collected bearing fault signal is successively introduced into two layers of programmable control filters with the same parameters as the two layers of analog filters, the difference between root mean square values of a low-pass output signal and a high-pass output signal of each layer of programmable control filter is used as a decision condition, and the current bearing fault signal is coded to obtain a current signal code; and comparing the current signal code with the simulation signal code to determine the current bearing fault signal type. According to the invention, the original continuous vibration signals collected on the motor can be directly classified, and the advantages of more convenient operation, faster classification speed, lower energy consumption and the like can be realized.

A video decoding method includes the steps of: generating a merge candidate list for a first block; selecting one among merge candidates included in the merge candidate list; and performing motion compensation for the first block based on motion information of the selected merge candidate. At this point, an inter-region merge candidate included in an inter-region motion information list may be added to the merge candidate list based on the number of spatial merge candidates and temporal merge candidates included in the merge candidate list.

This invention relates to the field of control methods for public transportation equipment, specifically to a control method for LED wall washer lights for driver fatigue wake-up in long tunnels. The method includes: calibrating driver fatigue-sensitive sections in each spatial unit of the entire tunnel and completing alignment; updating the vehicle's spatial unit and collected parameters in real time to classify the driver's real-time fatigue state; generating a fatigue wake-up light signal encoding parameter set for the vehicle corresponding to the current driving tracking ID, the current fatigue state, and the current spatial unit; and driving the wall washer lights to generate optical flow signals according to the set parameters. This invention constructs an optical flow signal framework deeply bound to the driving state, simultaneously achieving both fatigue wake-up and directional navigation functions. It also binds the driver's real-time fatigue state classification to a stepped stimulation level, ensuring that the optical flow signal only acts on the surrounding visual area corresponding to the tunnel sidewall, without interfering with the driver's observation. This spatial distribution eliminates the interference of dynamic lighting on normal driving observation.