541 results about "Impulse response" patented technology

The invention relates to an intelligent monitoring alarm method and system for a motor controller, and the method comprises the steps: obtaining an internal circuit signal and a body vibration signal of the motor controller, carrying out the combined noise analysis, and generating a dynamic noise baseline; performing component fault identification based on the dynamic noise baseline and the internal circuit signal to obtain a fault precursor current feature; performing component impact response separation based on the dynamic noise baseline and the body vibration signal to obtain hidden fault vibration characteristics; performing component association mapping on the fault precursor current feature and the hidden fault vibration feature to obtain an internal fault component identifier; and performing alarm analysis based on the fault component identifier, the fault precursor current feature and the hidden fault vibration feature to obtain a graded alarm decision. According to the invention, early fault features can be captured more sensitively, and false alarms and missing alarms are reduced.

The invention relates to the technical field of RFID tag signal optimization, and discloses an RFID tag signal optimization method and system based on deep learning. According to the method, feature extraction is carried out on a backscattering signal, core features of a multipath channel are quantized from a frequency domain and a time domain respectively, numerical representation of a channel state is further obtained, then obtained data information is used as input of a deep learning network, training and forward calculation are carried out, original emission parameters are adjusted, and a multi-path channel is obtained. Therefore, the conversion from blind extensive control to precise control of the transmitting end is realized, so that the problem of mismatching of parameter control and channel state caused by information splitting of the transmitting end and the receiving end in the prior art is solved; according to the signal optimization method for realizing joint adjustment of transmitting and receiving parameters through an end-to-end deep learning architecture, the optimization effect of an RFID tag signal in a complex environment is remarkably improved.

The embodiment of the invention provides an audio processing method and device, electronic equipment and a storage medium. The method comprises the following steps: determining a target pulse response of a first audio signal, wherein the target pulse response is a stereo pulse response used for simulating sound reflection and attenuation effects of the first audio signal in an acoustic space; performing convolution processing on the first audio signal and the target pulse response to obtain a second audio signal; and performing audio mixing on the first audio signal and the second audio signal to output a third audio signal. According to the scheme provided by the invention, the stereo pulse response data capable of simulating the reflection and attenuation effects of the sound in the space can be synchronously determined when reverberation is carried out on the audio signal, and reverberation is carried out on the audio signal by using the stereo pulse response data, so that the sound is heard to be generated in different space environments; the reverberation effect of the audio signal is more vivid, the sense of space and the sense of layering of the sound are increased, and the sound is fuller and stereoscopic.

The invention discloses a frequency domain ground penetrating radar transmitting source coding and receiving signal synthesis method and system. The method comprises the following steps: constructing a frequency domain coding continuous wave ground penetrating radar transmitting signal by extracting amplitude and phase information of multiple frequency points of a time domain ultra-wideband transmitting pulse; adopting a fast forward modeling method based on impulse response to realize forward modeling of a coding source emission signal of the typical geoelectric model; in-phase components and orthogonal components of all frequency points are extracted, frequency responses are synthesized into responses of quasi-time-domain transmitted pulses through an inverse Fourier transform method, the high resolution equal to that of time-domain ultra-wideband transmitted signals is obtained, and higher anti-noise performance is achieved. According to the invention, the amplitude phase coding continuous wave transmitting signal is adopted, so that the frequency spectrum shaping of the quasi-time domain pulse of the transmitting frequency spectrum is realized, the resolving power of the synthetic signal is improved, and a theoretical basis is laid for signal synthesis of frequency domain ground penetrating radar hardware design.

The present invention belongs to the field of mechanical engineering, and particularly relates to an equivalent model of a knocking kinematic pair of a continuous elastic body and a modeling method thereof. An equivalent model is established for the knocking kinematic pair in a continuous elastic body mechanical structure or system, that is, the non-linear mapping relationship between the knocking pulse force and the knocking initial velocity. By assuming that the knocking force pulse is a half-cycle sine wave, and simultaneously using the Hertz contact model and the origin transfer function or impulse response function of the mechanical structure at the knocking contact point to express the contact mechanical properties of the knocking pair material pair and the impedance properties of the mechanical structure at the knocking part, the relationship between the output and input of the non-linear equivalent model, that is, the knocking pulse force and the knocking initial velocity, is derived. Through the method of the present invention, the problem of rapid prediction of the knocking force pulse of a continuous elastic body mechanical structure can be solved.

Certain disclosed embodiments pertain to suppressing interference in a wireless communication system. For example, a method of suppressing interference can include receiving one, two, or more first signals including components from a plurality of sub-channels. Each of the first signals can be processed by a Finite Impulse Response filter adapted using an LMS update algorithm,

A motor fault prediction method for an HT80 general turbine controller comprises the steps that pressure signals of an inlet and an outlet of a hydraulic servo valve are obtained, and impulse response decomposition and time domain envelope analysis are conducted on the pressure signals to extract a microbubble nucleation characteristic spectrum in pressure fluctuation; and based on the microbubble nucleation characteristic spectrum, constructing a mapping relation between the bubble volume fraction and the system equivalent damping coefficient, and smoothing a damping coefficient time sequence through Kalman filtering to obtain a damping coefficient curve. And calling a hydraulic system pulse response model to calculate the instruction response time of the hydraulic servo valve according to the damping coefficient curve, and comparing the instruction response time with the adjustment target to obtain response delay. The lagging threshold curve is determined through experimental simulation calibration, whether the response delay exceeds the safety threshold or not is judged based on the lagging threshold curve so as to trigger an alarm, early warning of the hydraulic response delay trend is achieved, and the problem that millisecond-level rapid adjustment cannot be completed in operation can be avoided.

The invention relates to the field of sound equipment control, and discloses a sound field adaptive cloud control method and system based on deep learning, and the method comprises the steps: obtaining three-dimensional point cloud data corresponding to a sound field target space and physical layout parameters of a sound equipment array in the sound field target space; obtaining working parameter information when the sound array works in the sound field target space, and obtaining position information of the microphone array and impulse response data corresponding to the working parameter information detected by the microphone array in the sound field target space; and through a cloud sound field control model, according to the three-dimensional point cloud data of the sound field target space, the physical layout parameters of the sound array, the working parameter information of the sound array, the impulse response data detected by the microphone array and the position information of the aligned microphone array, determining the control parameter information of the sound array. According to the sound field adaptive cloud control method based on deep learning, the sound experience of a user can be improved.

The invention discloses a mobile underwater acoustic communication multipath channel modeling method based on sound field calculation, and relates to underwater sound waves. Channel modeling is carried out by inputting environmental parameters including an ocean sound velocity profile, submarine topography and the like, and modeling parameters including initial coordinates, motion trail equations and the like of a signal transmitting end and a signal receiving end. Performing ocean sound field calculation by adopting a ray tracing model, a normal wave model or a wave number integral model and the like, and calculating a sound field at each track sampling moment according to modeling parameters. And converting a frequency domain sound field result into a channel impulse response through inverse Fourier transform, and recovering the time-varying impulse response of the whole multipath channel by using local spline interpolation. And carrying out convolution on the transmitted signal and the time-varying impulse response of the multipath channel, and adding common propagation time delay to obtain a received signal simulation result. Through accurate sound field calculation and multipath channel modeling, the signal transmission condition in a specific marine environment can be simulated without actual marine environment measurement, the marine actual measurement cost is reduced, and the research and development efficiency is improved.

The invention provides a machine tool machining shaft anomaly detection method and system based on double-order excitation, and relates to the technical field of numerical control machine tools. The method comprises the steps that a key machining shaft of a numerical control machine tool is determined; constructing a shaft transmission anomaly detection model; a double-order reverse test sequence is injected into the key machining shaft through the controller, and a double-order pulse response sequence corresponding to the double-order reverse test sequence is recorded through the encoder; a pulse arrival time sequence is analyzed, and reverse response delay, static lag section length and speed transient characteristics are calculated; and inputting into a shaft transmission anomaly detection model for analysis, and outputting a reverse gap detection value of the key processing shaft. The technical problem that in the prior art, due to the fact that tiny anomalies of the numerical control machine tool are difficult to accurately detect, the machining anomaly detection precision is insufficient is solved, and the machining anomaly detection accuracy of the numerical control machine tool is improved through the double-order reverse test sequence and the shaft transmission anomaly detection model.

Linear unretimed interfaces lack clock and data recovery and retiming circuits implemented on a sophisticated digital signal processor. When the interface is not a retimed interface, it can be especially useful to extract some information about the link to allow for debugging and optimization of system deployment. An efficient solution can be implemented in unretimed interfaces to compute metrics such as the impulse response and signal histogram. Having the metrics allows for the solution to check and monitor the quality and the status of the link. Based on the link quality and status information, it is possible to address non-idealities and optimize performance of the unretimed interfaces and the link.

The invention discloses a flood discharge gate structure dynamic load time domain rapid identification and dynamic response field inversion method comprising the following steps: 1) carrying out a vibration test of a flood discharge gate structure, and obtaining a multi-source vibration response signal of the flood discharge gate structure; 2) constructing a unit impulse response matrix H and a load shape function matrix N; 3) establishing an inverse analysis model X = HNA for dynamic load time domain identification of the flood discharge gate structure; 4) inversely solving the load shape function coefficient matrix A to obtain a dynamic identification load of the flood discharge gate structure; and 5) inputting the identification load as an external load of the sluice structure to obtain an overall dynamic response field of the sluice structure.The method is based on the multi-source actual measurement vibration response of the sluice structure, the improved dynamic load time domain identification method based on the shape function is adopted, the time domain load of the sluice structure can be rapidly and effectively identified, and the identification accuracy is high.

Disclosed is an imaging method comprising obtaining a set of primary deconvolution kernels or a set of impulse responses relating to an optical system used to capture said image; obtaining said image signal, said image signal being subject to one or more imaging effects including at least one or more non-isoplanatic imaging effects; performing a low-rank approximation on said set of primary deconvolution kernels or impulse responses to determine respectively a set of deconvolution modes or a set of impulse response modes, each deconvolution mode comprising a modal secondary deconvolution kernel and a modal weight function and each impulse response mode comprising a modal impulse response and a modal inverse weight function; obtaining at least approximated imaging effect-free object information related to said object by applying said modal secondary deconvolution kernels and modal weight functions or said modal impulse responses and modal inverse weight functions to said image signal.

The present invention relates to methods and systems for improving the efficiency of artificial neural networks by configuring them to implement linear dynamical systems that compute state updates in linear time. More specifically, the present invention specifies methods and systems for setting the weights of least one linear artificial neural network layer by (a) selecting an set of basis vectors that define a desired impulse response for the layer, (b) deriving a matrix that produces this desired impulse response over a target temporal window, (c) deriving a matrix that dampens the impulse response to zero outside of the target window, and (d) combining these two matrices together through addition to obtain the layer's recurrent weights. Systems composed of at least one such linear layer are applied to a time series of input data elements to produce outputs that encode the results of pattern classification, signal processing, data representation, and data generation tasks.

The invention discloses a natural language processing technology-based cultural and creative element data analysis method, which comprises the following steps of: based on AI intelligent plush doll interaction data, generating a cultural and creative structure embedding degree index through named entity recognition and semantic network topology analysis; an impulse response function is constructed based on the cultural creative structure embedding degree, and a cultural creative memory cycle index is calculated in combination with the path length and information backflow; fusing the multi-modal features and the ideal innovation region, and outputting a perception novelty score; screening high-potential-energy elements to construct a semantic sub-graph, simulating a thermodynamic process, and identifying a text-creative fusion hotspot chain; and decoding the hotspot chain into a design semantic tag, matching a material database to generate an appearance scheme, and converting the appearance scheme into an interaction template, thereby realizing a customized design closed loop from a user dialogue to a doll form and behavior. Through data driving and cross-modal analysis, implicit culture preferences in user dialogues are dominated, and creativity of the appearance of the AI intelligent plush doll and humanization of interaction are improved.

The invention discloses a transducer electric pulse response measurement and correction method, system and device, and relates to the technical field of photoacoustic imaging, and the method comprises the steps: collecting a photoacoustic signal generated by a microsphere through a transducer; performing uniform grid division on the ith array element of the transducer and the to-be-reconstructed imaging area, and calculating the spatial pulse response of the ith array element at the microsphere position; calculating the electric pulse response of the ith array element by using the spatial pulse response and the Fourier transform of the photoacoustic signal so as to construct a correction matrix of the ith array element, and summing and averaging the correction matrixes of all the array elements to obtain an average correction matrix; when any object is imaged, the to-be-deconvoluted photoacoustic signals collected by each array element are multiplied by the average correction matrix to obtain restored photoacoustic signals; according to the response correction method, system and equipment, after the electric pulse response of the transducer is accurately measured, deconvolution of the signal domain is carried out, the image is reconstructed, and the image quality is improved to a certain extent.

The invention belongs to the field of sound field environment modeling, and particularly discloses a room impulse response simulation method and system based on a generative adversarial network. The method comprises the following steps: carrying out convolution on a public room impulse response data set and a pure audio data set, and adding noise at the same time to obtain a reverberation audio training data set; inputting the constructed reverberation audio training data set into a physical parameter estimation network for pre-training, calculating a loss function of the network, and adjusting network parameters through gradient back propagation; and freezing the physical parameter estimation network, jointly training the generative adversarial network, taking the pre-trained physical parameter estimation network as a physical constraint module, and guiding a generator in the generative adversarial network to output a room impulse response conforming to a physical rule. According to the invention, the problem of distortion of the generated pulse response can be effectively reduced, and the generated pulse response is closer to real data.

The present disclosure relates to the technical field of audio control. Provided are a computer-implemented method for audio control, and an electronic device and a storage medium. The computer-implemented method for audio control comprises: on the basis of a specified measurement signal, performing acoustic effect testing on a target space, in order to obtain environmental response information, wherein the environmental response information comprises impulse response information and post-separation impulse response information; analyzing the environmental response information, in order to obtain acoustic characteristic information of the target space; on the basis of the acoustic characteristic information, performing compensation processing on audio to be processed, in order to obtain regulated audio; regulating gains of multiple channels corresponding to the regulated audio, in order to obtain re-regulated audio; and performing multi-channel collaborative optimization processing on the re-regulated audio, in order to obtain audio having a target effect. The method achieves precise compensation for spatial acoustic defects, resolves inter-channel crosstalk, improves the acoustic image localization and spatial perception, significantly improves the perceptual audio quality, and optimizes an output.

The present disclosure provides a method for realizing a speaker array-oriented multiple filter system and a related device, belonging to the technical field of audio systems. The method includes: merging, before real-time audio processing, filters of a plurality of sound effect modules in an audio signal processing flow offline to form a finite impulse response (FIR) multiple filter network. The present disclosure places most of computation in an offline processing flow by merging the filters of the plurality of sound effect modules in offline convolution, so that the computation amount of real-time processing is greatly reduced.

A 3D neural radiance field (NeRF) is used to generate an impulse response (IR) characterization, which can then be input to a convolutional reverberation engine to create an audio experience that reflects the in-game world on a 2.0 stereo speaker system. The NeRF recreates a background geometry and the impulse response of a virtual 3D space generated using NeRF is input to the convolutional reverberation engine to transform game sounds / music to appear as though they are occurring inside the 3D space of the game. The same may be done for the player's real-world space in which the virtual IR and real IR are blended together in real-time, and the real-life player tracked as he moves around the room to create audio as it would sound were the player moving through the virtual space while adjusting for the acoustics of the real space.

The invention relates to the technical field of automatic control, in particular to a switching positive system identification method and system and a storage medium, and aims to solve the problems that in the prior art, a model violates non-negative physical constraints, hyper-parameter estimation is prone to local optimum, calculation efficiency is low, and switching path identification precision is insufficient. The method comprises the following steps: firstly, determining non-negative priori of a system model and pulse response truncated Gaussian distribution through a preparation module; constructing a Bayesian network, and iteratively optimizing a switching path by adopting Gibbs sampling; and finally, based on regularization optimization and Gibbs sampling in combination with Monte Carlo approximation, accurately estimating the pulse response of the subsystem. According to the method, the non-negative characteristics are embedded into the whole identification process, global parameter optimization is achieved, high-dimensional integral calculation is simplified, identification precision and stability are improved, and the method is suitable for multi-scene engineering application.

Data transceivers including a transmitter configured with a digital filter, and a receiver configured with an equalizer, are equipped with logic to measure a combined pulse response to a symbol generated by the transmitter at an output of the equalizer, adjust the combined pulse response by an impulse response of the digital filter to generate an adjusted pulse response, and modify the digital filter with one or more floating taps based on the adjusted pulse response.

A distributed ultra-wide band (UWB) radar system and methods for operating the same are disclosed. The distribute radar system uses a plurality of separate UWB radios or nodes that do not use a centralized clock or source of time. However, the distributed UWB system operates to provide radar-like functionality and fine-grain sensing capabilities through synchronization based on line-of-sight (LOS) signal processing and noise estimations. Synchronized channel impulse responses (CIRs) can be processed for general object detection and tracking, gesture recognition, or even micro-motions such as monitoring vitals

The embodiment of the invention discloses a high-precision sparse estimation method for a shallow sea multipath channel, and the method comprises the steps: constructing a discretized channel input and output relation based on a coherent multipath channel model, constructing a measurement matrix through employing a transmitted signal, and converting the discretized channel input and output relation into a sparse representation model in a rectangular vector form; according to the method, in the process of solving the sparse solution of the target function for the first time, a multi-step forward search strategy is utilized to carry out all K iterations, and then the sparse solution is obtained, so that more accurate channel time domain impulse response is obtained through estimation.

The present invention discloses an improved broadband shortwave channel simulation calculation method based on ITS, comprising the following steps: step 1, random modulation function simulation: step 2, phase determination function simulation: step 3, improved delay power distribution function simulation: step 4, defining the time-varying pulse response as a function of time and delay variables. The method disclosed by the present invention improves the delay power distribution function in the ITS channel model, making its calculation process simpler, thereby realizing the simulation calculation of broadband shortwave channels more quickly and conveniently, and the obtained shortwave channel model takes into account the shortwave signal delay and Doppler expansion effect caused by the ionosphere, and can simulate and calculate the shortwave link channel in any region of the world.

The invention relates to vehicle cabin simulation for audio tuning and testing. A method of simulating a vehicle cabin for audio tuning and / or testing and a corresponding system, the method comprising obtaining (17) and storing (20) 3D impulse responses corresponding to individual loudspeakers in the vehicle cabin to be simulated. At a location remote from the vehicle, a multi-channel input audio stream (22) is generated and the individual channels are processed (23) by a real-time convolution process to create an audio stream in surround sound format as output. An audio stream output (24, 32), e.g. In a panoramic sound format, may be decoded (33) and played back in the audiometry room so that a tuning engineer may adjust parameters of the input audio stream (22, 28) delivered in real time to the simulated environment listening experience. In this way, the parameters can be optimized and applied back to the sound system of the real-world vehicle.

The invention discloses a tool and model testing method based on TTS, and belongs to the technical field of intelligent terminal testing. According to the method, the TTS technology is combined with natural language generation, environment simulation and a self-adaptive algorithm, a test text set containing sentence pattern variants and synonym replacement is generated through a natural language generation model, a parameter-adjustable TTS engine is used for synthesizing voice signals with acoustic and emotional characteristics, the voice signals and an environment impulse response function are subjected to convolution superposition of scene noise and then input into a terminal, and the voice signals are converted into voice signals with the acoustic and emotional characteristics. Mapping to a semantic vector space to calculate similarity, and finally generating an iterative test strategy according to the confusion matrix. According to the scheme, test text automatic generation, complex environment simulation and test strategy adaptive optimization are realized, the test efficiency and coverage are improved, the problem is accurately positioned, the multi-scene adaptability is enhanced, and a full-process intelligent test scheme is formed.

A method of simulating a vehicle cabin for audio tuning and / or testing. The method includes obtaining and storing a 3D impulse response corresponding to each speaker within the cabin of a vehicle to be simulated. The method includes at a location remote from the vehicle, in real-time, applying convolution processing on each channel of a multichannel audio stream based on the corresponding 3D impulse response. The method includes outputting a surround sound format audio stream.

Methods and systems are disclosed for an audio system for a vehicle system. In one example, a noise cancellation system includes a vehicle having a plurality of speakers and a plurality of microphones, a plurality of sensors, and a controller. The controller includes instructions stored on non-transitory memory that when executed cause the controller to generate a noise cancellation signal using a set of head-related impulse responses for the plurality of speakers and the plurality of microphones based on a head position of one or more occupants and a plurality of transfer functions, including to selectively update only a subset of the plurality of transfer functions responsive to the plurality of sensors detecting head movement greater than a threshold.

The invention provides a space target orbit maneuver identification method and system based on adaptive LSM, and the method comprises the steps: obtaining the orbit data of a space target, calculating the six orbit elements based on the orbit data, and coding the six orbit elements into a pulse sequence; and inputting the pulse sequence into an improved adaptive LSM for detection to obtain an orbit maneuver behavior identification result of the space target. According to the method provided by the invention, six orbital elements are calculated through the speed and the position of the orbital, then the orbital parameters are input into an improved LSM, and the improved LSM adopts an adaptive threshold neuron as a calculation unit, so that the threshold can be dynamically adjusted according to the current pulse response and attenuated along with time; meanwhile, an improved particle swarm optimization algorithm is combined to carry out optimization setting on an initial value of a neuron, so that the initial performance of the model is improved; and a learnable neuron connection weight based on an attention mechanism is introduced, so that the accuracy and reliability of orbit prediction are improved.