137 results about "Linear filter" patented technology

A data channel on an integrated circuit device includes a non-linear equalizer having as inputs digitized samples of signals on the data channel, decoding circuitry configured to determine from outputs of the non-linear equalizer a respective value of each of the signals, and adaptation circuitry configured to adapt parameters of the non-linear equalizer based on respective ones of the value. The non-linear equalizer includes a non-linear filter portion, and a front-end filter portion configured to reduce numbers of the inputs from the digitized samples. The non-linear equalizer may be a neural network equalizer, such as a multi-layer perceptron neural network equalizer, a reduced complexity multi-layer perceptron neural network equalizer, or a radial-basis function neural network equalizer. Alternatively, the non-linear equalizer may include a linear filter and a non-linear activation function, which may be a hyperbolic tangent function.

Multiple successively spatially downsampled versions of a rendered image frame are generated for at least one two-dimensional signal component of one or more two-dimensional signal components of an image frame, and one or more versions of the rendered image frame are selected from among the rendered image frame and the spatially downsampled versions of the rendered image frame for sampling a texture feature based, at least in part, on a prediction computed by a neural network.

The invention discloses a coordinate system transformation fusion filtering tracking method and system for a dual-base-station radar, and relates to the technical field of radar target tracking. The method comprises the following steps: firstly, establishing a state and observation equation, and determining an initial state of a target based on prior information under Cartesian coordinates; then, obtaining a target motion state through one-step prediction, generating a sigma point by utilizing U transformation, and calculating a mean value and a covariance for constructing state space prediction; thirdly, fusing the measurement data and the prediction data by using a Kalman filter to obtain optimal state estimation and a covariance matrix; and finally, converting the updated state estimation back to the Cartesian coordinate system based on U transformation, and circulating the process until the tracking is finished. According to the method, the nonlinear filtering problem in the updating process can be avoided, and the tracking robustness and precision are improved.

The invention discloses an aircraft robust relative navigation method based on mixed distribution under non-Gaussian noise, and belongs to the technical field of calculation, reckoning or counting. In order to solve the problem that non-stationary heavy tail noise caused by a time-varying environment in a relative navigation process of an aircraft generally causes filtering divergence, Dirichlet random mixed vectors are introduced to fuse Gaussian, student t and multivariate K distribution, so that a Gaussian-student t-multivariate K mixed distribution modeling measurement likelihood is provided; and then the KLD of the real posterior probability density function and the approximate posterior probability density function is minimized through the variational Bayesian technology to solve the relative motion state of the aircraft and approximate posterior estimation of filter parameters, the state quantity information of the target relative to the aircraft is obtained, and the relative position and speed are solved. Finally, a nonlinear filter based on Gaussian-student t-multivariate K mixed distribution is deduced, the relative navigation precision is improved, and the nonlinear filter is used for angle-measurement-only relative navigation of an aircraft in a time-varying environment.

Audio enhancement of musical content is performed by a device coupled to a network. The device receives an audio signal to be transmitted over the network, and detects when musical content is present in the audio signal based on a content probability threshold. The device disables noise suppression for the audio signal and applies a linear filter to cancel echo for the audio signal. The device disables gain control for the audio signal and encodes the audio signal using a codec designed for music.

Disclosed is a coherent optical transceiver for optical communication including a transmitter, a receiver, and a PIC. The transmitter includes a DAC and a driver. A modulator in the PIC limits a signal spectrum of an output optical signal within a Nyquist frequency band. The receiver receives an input optical signal from the PIC and converts the input optical signal to an input analog electrical signal. An ADC converts the input analog electrical signal into an input digital electrical signal indicative of the input optical signal at an ADC sampling rate. The DSP includes a linear filter to equalize intersymbol interference, a post filter, and an MLSE to determine symbols corresponding the input optical signal. The driver and the post filter are first order filters with transfer function G(z)=1+az−1, where a is between 0 and 1.

The invention provides an OBD message analysis and attitude rendering method and system based on a vehicle dynamics model, and belongs to the field of vehicle electronics and control. The method comprises the steps that a message is analyzed through an OBD interface, and vehicle operation parameters are obtained; establishing a unified time base and carrying out resampling and synchronous processing on the data of each channel; constructing a fifteen-degree-of-freedom vehicle dynamics model comprising a vehicle body six-degree-of-freedom pose, a vehicle body angular velocity, a four-wheel rotation angular velocity and unsprung mass vertical displacement for state prediction; designing an observation function to map a model state to an OBD observation space, and adopting an observability enhancement strategy; predicting and observing data are fused by using a nonlinear filter, and abnormal observation gating is carried out based on a mahalanobis distance and an amplitude threshold value; compensating system time delay and adaptively adjusting observation noise; and performing three-dimensional real-time rendering on the attitude information. According to the method, high-precision and high-robustness vehicle attitude estimation can be realized only by depending on the OBD message, and the system cost is effectively reduced.

Methods for video decoding and encoding, apparatuses and non-transitory computer-readable storage media thereof are provided. In one method for video decoding, a decoder may obtain a plurality of first motion compensated samples of a first channel and a plurality of second motion compensated samples of a second channel for a current inter coding block, obtain a non-linear filter, and obtain a plurality of filtered motion compensated samples of the first channel based on the non-linear filter, the first motion compensated samples of the first channel, and the second motion compensated samples of the second channel.

In various examples, the present disclosure relates to using temporal filters for automated real-time classification. The technology described herein improves the performance of a multiclass classifier that may be used to classify a temporal sequence of input signals—such as input signals representative of video frames. A performance improvement may be achieved, at least in part, by applying a temporal filter to an output of the multiclass classifier. For example, the temporal filter may leverage classifications associated with preceding input signals to improve the final classification given to a subsequent signal. In some embodiments, the temporal filter may also use data from a confusion matrix to correct for the probable occurrence of certain types of classification errors. The temporal filter may be a linear filter, a nonlinear filter, an adaptive filter, and / or a statistical filter.

The invention discloses an audio authenticity identification method and device based on a dual-path Transform, and the method comprises the following steps: preprocessing: converting an original audio signal into time-frequency representation, and extracting features through LFCC or STFT to obtain the time-domain features and frequency-domain features of the audio signal; the time-frequency representation feature = {B, F, T} containing time domain features and frequency domain features is obtained through preprocessing, B is the batch size, F is the number of frequency channels equal to the number of LFCC linear filters, and T is the number of time frames; the convolution encoder is used for encoding the input time-frequency representation through a plurality of 2D convolution layers and extracting local features; and respectively processing the frequency domain information and the time domain information through a double-path Transform structure to form semantic-acoustic information decoupling. Frequency domain information and time domain information are respectively processed through a double-path Transform structure, and efficient decoupling of semantic information and acoustic information is realized in combination with an attention mechanism, so that audio information of different levels is better extracted and utilized.

The invention discloses an improved method for calculating grazing incidence sea surface back scattering through a small slope approximation method, and belongs to the technical field of sea surface electromagnetic scattering calculation, and the method comprises the following steps: S1, determining the wind speed of each stage of sea condition, and calculating the seawater dielectric constant; s2, generating sea surface geometry by using a linear filtering method based on a sea wave spectrum according to the determined wind speed; s3, introducing a conical incident wave; s4, introducing an edge geometric attenuation function; and S5, calculating sea surface back scattering by using an approximate integral formula of a small slope approximation method. According to the improved method for calculating grazing incidence sea surface back scattering through the small-slope approximation method, the edge geometric height is attenuated to 0 by applying the edge geometric attenuation function, so that the situation that the height fluctuation of the sea surface edge is close to an incident wave energy central axis is avoided, the problem that the calculation result is large under grazing incidence is solved, and the calculation efficiency is improved. And meanwhile, the calculation result is more accurate.

The present invention discloses a hybrid active noise cancellation superposition method based on a neural network, including: W f W(n) or / and W b (n) is implemented by a linear filter FIR or IIR, and the filter parameters are iterated according to the LMS or RLMS algorithm. Since S(z) is non-linear, S’(z) can still be estimated by a neural network, and the parameters of the neural network are iteratively solved according to the BP algorithm. For the non-linear link existing in the path of the original noise propagation from the A-bit noise source to the B-bit speaker, such as the case where the original noise is too large, resulting in non-linearity of the device, if the feedforward filter can use a non-linear filter, it can better control the noise; for the non-linear link existing in the control channel from the C-bit error microphone to the B-bit speaker, such as the non-linearity of the error microphone or the non-linearity of the amplifier, if the feedback filter can use a non-linear filter, it can better control the noise.

A computer-implemented method for controlling a system based on a trend detected in a data time series acquired by a sensor. The method includes: acquiring and providing a data time series by a sensor; applying at least one linear filter function with a resolution L to each point in time of the data time series and obtaining a characteristic value for quantifying the temporal development of the data time series for each resolution L; detecting a trend in the data time series when one of the characteristic values of the data time series reaches a threshold value; and triggering a response of the system when a trend has been detected in the data time series.

Systems and methods for compensating a transmit signal for charge trapping effects of a power amplifier are provided. In certain embodiments, a non-linear filter is trained based on time aligning a first set of observations taken from digital transmit data prior to conversion to a radio frequency transmit signal, and a second set of observations taken from an output of a power amplifier that amplifies the radio frequency transmit signal. In certain implementations, the first set of observations and the second set of observations are obtained without decimation. Rather, decimation is provided after timing alignment. By implementing the DPD system in this manner, signal data is not lost by decimation and more accurate timing alignment between the sets of observations is achieved.

The invention relates to a clutter signal generation method and device. The method comprises the following steps: generating two groups of uniformly distributed random sequences u1 and u2; converting the two groups of uniformly distributed random sequences into a Gaussian white noise sequence through a Box-Muller algorithm; generating a Gaussian color noise sequence from the Gaussian white noise sequence through a linear filter; performing nonlinear transformation on the Gaussian color noise sequence to obtain a clutter basic model sequence; and performing amplitude modulation, distance modulation and speed modulation on the clutter basic model sequence to generate a clutter signal with amplitude, time domain and frequency domain information. According to the invention, amplitude modulation, distance modulation and speed modulation are respectively carried out on the clutter basic model sequence by using the clutter sequence modulation module, so that the generated clutter signal has amplitude, time domain and frequency domain information coupled with a simulation scene, and the accuracy and fidelity of clutter simulation are improved.

The invention belongs to the technical field of image processing, and discloses a single-source domain generalization medical image segmentation method and related device based on domain randomization, and the method comprises the steps: inputting a to-be-segmented medical image into a pre-trained segmentation network model, and obtaining a segmentation result of the to-be-segmented medical image; the segmentation network model comprises a global intensity nonlinear filter, an encoder and a decoder; a uniform low-frequency spectrum transformation filter is arranged in the encoder and is used for performing mixing operation on low-frequency components of the spectrum of the input image by using Bernoulli distribution according to statistical magnitude sampled from uniform distribution to obtain a disturbance low-frequency component and combining the disturbance low-frequency component with high-frequency components of the spectrum of the input image to obtain an augmented spectrum; and the decoder is used for fusing the input image, the feature map of the input image, which passes through the downsampling of the convolutional layer, and the multi-resolution feature map from the encoder through step-by-step upsampling, and generating a pixel-by-pixel segmentation result of the input image through the convolutional layer and an activation function, thereby improving the image segmentation capability of an unknown domain.

The invention discloses a master node assisted slave node navigation positioning method, relates to a master node assisted slave node navigation method, and belongs to the field of underwater vehicle navigation positioning. The invention aims to solve the problem of poor low-precision node positioning effect caused by the fact that the influence of a node navigation path and a relative navigation path between interactive nodes on the low-precision node positioning precision is not considered when low-precision node positioning error correction is realized by adopting a non-linear filtering algorithm in the prior art. The invention provides an improved navigation algorithm of a low-precision moving node under the assistance of a high-precision node. The method comprises the following steps: screening observation data, adaptively predicting a state covariance matrix in one step through selection of observability so as to improve the requirement of slave node navigation precision, establishing a slave node navigation system model and a process framework under the assistance of a master node, and correcting a self-navigation position state of a low-precision node by adopting an extended Kalman filtering improved algorithm. And the low-precision node positioning precision is improved.

Methods for video decoding and encoding, apparatuses, and non-transitory computer-readable storage media are provided. In one method, a decoder may at least one block vector (BV) based on at least one BV candidate list for an intra template matching prediction (IntraTMP) mode. Additionally, the decoder may obtain a prediction block for a current block based on the at least one BV, or based on the at least one BV and a linear filter of a local illumination compensation (LIC) mode.

Methods, apparatus, and non-transitory computer-readable storage media for video decoding and encoding are provided. In a method for video decoding, a decoder may obtain a plurality of first motion compensation sample points of a first channel and a plurality of second motion compensation sample points of a second channel for a current inter-frame coding block, obtain a nonlinear filter, and obtaining a plurality of filtered motion compensation samples for the first channel based on the non-linear filter, the first motion compensation samples for the first channel, and the second motion compensation samples for the second channel.

A noise reduction system for actively compensating background noise in a passenger transport area of a vehicle. The noise reduction system includes a nonlinearity filter unit having a model of a non-linear transfer function of the sound generator, wherein the nonlinearity filter unit is configured to receive the anti-noise signal and to generate a filtered anti-noise signal by applying a non-linear filter function on the anti-noise signal, which is based on the model of the non-linear transfer function in that the non-linear response of the sound generator is at least partially corrected when driven by the filtered anti-noise signal. Wherein the nonlinearity filter unit is further configured to output the filtered anti-noise signal to a sound generator.

A memory device is operated using a reduced row address space (e.g., 48k rows per bank vs. a full capacity 64k rows per bank). The unused address space (e.g., 16k rows) is used and mapped by the memory device to store information for at least some of the bad rows. In this manner, many more bad rows may be "repaired" at the expense of a reduction in the capacity of the memory device. The translations of external row addresses to internal physical row addresses may include permuting row addresses within groups of row addresses to avoid bad rows within respective groups of row addresses. A linear filter (e.g., Bloom Filter, XOR filter, etc.) may be used to store information for the translations of external row addresses to internal physical row addresses. The information for the translations may be determined and programmed into the memory device once during manufacturing.

The invention discloses an echo cancellation processing method and device in a scene with large loudspeaker loudness, and belongs to the field of voice signal processing. The echo cancellation processing device is installed in equipment and comprises an audio acquisition module, a self-adaptive threshold compression module, a delay determination module, a delay compensation module, an echo cancellation module and an audio playing module. The echo cancellation method comprises the following steps: when equipment runs on line, the audio acquisition module acquires a reference signal sent by far-end equipment and a near-end microphone signal, and inputs the reference signal and the near-end microphone signal into the adaptive threshold compression module to compress the amplitude of the microphone signal; meanwhile, according to the delay tau stored in advance, delay compensation is carried out on the far-end reference signal through a delay compensation module; and finally, performing block frequency domain adaptive filtering on the signal subjected to the compression amplitude limiting processing and the far-end reference signal subjected to the compensation delay through an echo cancellation module, and performing echo cancellation. According to the method, the convergence speed of the linear filter is higher and more stable.

The present invention provides an echo cancellation method in a delay jitter scenario in the field of echo processing technology, comprising: step S10, collecting a far-end signal and a near-end signal; step S20, calibrating and aligning the far-end signal and the near-end signal through a delay calibration module and then inputting them into a linear filtering module; step S30, the linear filter of the linear filtering module outputs a linear filter coefficient and an error signal to a far-end signal synthesis unit based on the far-end signal and the near-end signal; step S40, the far-end signal synthesis unit calculates a far-end reference signal and a delay state based on the linear filter coefficient, and outputs the far-end reference signal, error signal and delay state to a nonlinear suppression module; step S50, the nonlinear suppression module outputs an echo-free signal based on the far-end reference signal, error signal and delay state. The advantages of the present invention are: it realizes compensation for the delay jitter of the echo, greatly improves the echo cancellation effect, and thus greatly improves the call quality.

The invention discloses a method and system for improving low signal-to-noise ratio direct sequence spread spectrum signal code tracking performance, and the method comprises the steps: generating an I-path bipolar code information source, and obtaining a baseband signal; performing convolution operation with the matched filter coefficient to obtain a matched filtering result; time lag and time lead are respectively carried out according to a specified length, so that a lag branch signal and a lead branch signal are respectively obtained; coherent integration is carried out on the local pseudo code sequence at a PL end, and an envelope value is solved; setting an incoherent accumulation length at a PS end, performing incoherent accumulation operation on the envelope value, and selecting a code phase discrimination mode to obtain a code phase discrimination value; and a phase change value is obtained through the linear filter and a loop filter of the code loop, and the phase change value is used for correcting the NCO of the local pseudo code sequence to realize closed-loop feedback. Code tracking performance is improved, signals can be accurately transmitted in a complex interference environment, error codes are reduced, inter-symbol crosstalk is effectively reduced, signal decoding accuracy is improved, and communication quality is guaranteed.

The application discloses a linear filtering algorithm optimization method based on a depth separable convolution idea, and comprises the following steps: S1, generating the weight of a filter kernel according to a selected linear filtering algorithm and a set filter kernel size; S2, filling the image boundary according to the set filter kernel size; S3, processing an input image according to the channel number of the input image; S4, merging the multi-channels after the linear filtering operation, and outputting the filtered image; S5, using mean square error, peak signal-to-noise ratio and structural similarity as indexes to analyze the image quality of the output filtered image; and S6, comparing the linear filtering algorithm with a naive linear filtering algorithm, a linear filtering algorithm based on a row-column separation idea and a linear filtering algorithm of an OpenCV library based on a buffer and the row-column separation idea. The application can effectively adapt to various hardware environments without the need of making a large number of modifications for specific chips.

The present invention discloses a high-precision spectral confocal microscopy imaging system, comprising a light modulation module, a spectrum splitting module, a scanning imaging module, an image detection device and a computer. The light beam emitted by the light modulation module passes through the scanning imaging module and is incident on a sample to excite a fluorescence signal. The fluorescence signal passes through the spectrum splitting module and is received by the image detection device. The image detection device converts the current signal into a digital signal and transmits it to the computer to complete imaging. The system is characterized in that the spectrum splitting module consists of a first converging lens, a first pinhole, a first linear long-wave pass filter, a second converging lens, a first linear short-wave pass filter and a third converging lens arranged in sequence. The system has the advantage of realizing high-precision spectral confocal imaging by combining lenses and linear filters on the basis of the traditional confocal microscopy imaging principle, solving the problem of spectral crosstalk in confocal imaging, and achieving a spectral resolution of less than 3.0 nm.

The present invention relates to a method for segmenting fundus image blood vessels based on linear filtering and deep learning, belonging to the field of medical image processing. The method includes: S1: Input the fundus image, and use the linear filtering algorithm based on the Hessian matrix to enhance the blood vessel area; S2: Use MobileNetV3 as the basic model of the blood vessel segmentation model, establish the segmentation network VSegNet, and then perform downsampling by adding an encoder based on the recursive module to the segmentation network VSegNet; S3: Add a decoder to the segmentation network VSegNet to perform upsampling and aggregation on the feature map output by the encoder; S4: When training the segmentation network VsegNet, calculate the loss value of the segmentation result by using the L1 norm of the segmentation prediction result and the segmentation ground truth image. The present invention strengthens the feature information extraction ability, thereby improving the model segmentation performance.

A method of operation of a texturing / shading unit in a GPU pipeline is used for efficient convolution operations. The method uses texture hardware to collectively fetch all the texels required to calculate properties for a group of output pixels without any duplication. The method then bypasses bilinear filter hardware in the texture hardware and passes the fetched and unfiltered texel data from the texture hardware unit to shader hardware in the texturing / shading unit. The shader hardware uses the fetched texel data to perform a plurality of convolution operations to calculate the properties of each of the output pixel.

The invention provides a self-adaptive modulation and coding method for rapid convergence of an ad hoc network of an unmanned ship, which comprises the following steps of: S1, measuring channel quality, acquiring a channel condition, and acquiring HARQ / CRC (Hybrid Automatic Repeat reQuest / Cyclic Redundancy Check) feedback according to a current MCS (Modulation and Coding Scheme); s2, performing an inner loop link adaptive algorithm by combining a dynamic linear filtering mechanism based on a greedy algorithm according to the channel condition to obtain an illaSINR value; and S3, carrying out an outer loop link adaptive algorithm based on HARQ / CRC feedback and the target BLER, and obtaining an ollaSINR value. And S4, integrating the illaSINR value and the ollaSINR value, obtaining a decision MCS (Modulation and Coding Scheme), and carrying out adaptive modulation coding based on the decision MCS. According to the invention, rapid convergence and stable operation of the unmanned ship ad hoc network communication system are realized.

The application relates to an audio signal enhancement method and device, computer equipment and a storage medium. The method comprises the following steps: when a voice packet is received, sequentially decoding and filtering the voice packet to obtain an audio signal; when the audio signal is a forward error correction frame signal, extracting a feature parameter from the audio signal; converting the audio signal into a filter speech excitation signal based on a linear filtering parameter obtained by decoding the voice packet; performing speech enhancement processing on the filter speech excitation signal according to the feature parameter, a long-time filtering parameter and a linear filtering parameter obtained by decoding the voice packet, to obtain an enhanced speech excitation signal; and performing speech synthesis based on the enhanced speech excitation signal and the linear filtering parameter to obtain a speech enhancement signal. The method can improve the timeliness of audio signal enhancement.