154results about How to "Good anti-noise performance" patented technology

The invention relates to an image mosaic method based on neighborhood Zernike pseudo-matrix of characteristic points, which leads image statistical information (Zernike pseudo-matrix) to be interrelated with the characteristic points of an image by using the following steps: firstly, extracting interest points of an inference image and an input image by utilizing a Harris angle detector, and taking rectangular neighborhoods using the interest points as a center as a local characteristic region with characteristic matching; secondly, calculating the Zernike pseudo-matrix to the rectangular characteristic regions to be used as descriptors of the characteristic region, and realizing the matching of the characteristic points through comparing the Euclidean distance of the characteristic vector of the descriptor of each characteristic region. The matching can have less wrong matching points which are eliminated through a RANSAC (RANdom Sample Consensus) algorithm, and the right matching relation can be calculated to realize the image mosaic. The invention can effectively realize the image registration and mosaic with geometric transformation relations of translation, rotation, small scale zooming, and the like, and can be used for image treatment and image synthesis of fields such as communication, multimedia technology, and the like.

The invention belongs to the technical field of digital signal processing and provides a linear frequency-modulated parameter estimating method with high precision, low complexity, high speed and high efficiency and an implementing device thereof. The invention adopts a technical scheme that: by means of an energy barycentre interpolation estimation and Radon ambiguity transformation (RAT) based modulating frequency estimating method, the method mainly comprises the following steps of: for a given input signal s(n), calculating an ambiguity function AFs(tau, xi) of the input signal s(n); exchanging scanning straight lines xi=k tau continuously; figuring out the projection of AFs(tau, xi) on the scanning straight lines by means of Radon transformation; recording all projection values; constructing a panorama discrete spectrum; searching out the peak position of the panorama discrete spectrum; estimating the projection value of the actual peak value; obtaining the estimated value of thesignal modulating frequency; searching out the peak value spectrum of a fractional order Fourier spectrum; and figuring out the energy barycentre position of the spectrum so as to estimate the signalbarycentre frequency. The method is mainly applied to the linear modulating frequency signal parameter estimation in the digital signal processing.

A method for accurate and rapid automated detection of atrial fibrillation (AF), sinus rhythm (SF), and atrial flutter (AFL) is disclosed, which allows distinguishing of these cardiac signals with lowered risk of errors by implanted pacemakers and like devices. The method includes training episodes of intra-cardiac signals (called the closed data set CDS) to evaluate five feature parameters with a discriminator classifying the signal into AF, AFL or sinus rhythm (SR). Comparison with the independent decisions of experienced physicians for each episode reveals specificity, accuracy and sensitivity of greater than 97%. Each episode is a window of intracardiac signal of interval 1-2 seconds with the discriminator providing results in less than 0.25 s. In another aspect, the method is resistant to the presence of noise in the data. In yet another aspect, more feature parameters may be used in alternative implementations including for detecting signals other than AF, AFL & SR.

Circuits and methods are provided for transmitting a pseudo-differential output signal with relatively high immunity to noise and jitter. The output driver of the invention receives two differential input signals and outputs a single output signal with low voltage transistors and programmable impedance and on-die termination circuits. The pseudo-differential output driver consumes little circuit area and has low output capacitance.

A stacked type semiconductor device comprising: a baseboard having a terminal row formed at an end in which connecting terminals is arranged linearly and having a wiring pattern connected to the connecting terminals and external terminals; semiconductor chips having a pad row in which pads is arranged linearly in parallel to the terminal row and being stacked on the baseboard; and interposer boards having a wiring layer including a plurality of wires arranged in parallel with the same length for connecting between pads of the pad row and connecting terminals of the terminal row.

A voltage measurement device includes a first group of switches Q1, Q2, a second group of switches Q7, Q8 and a third groups of switches Q5, Q6. By turning on the third group of switches Q5, Q6, the first group of switches Q1, Q2 are turned on, so that a condenser C1 is charged by voltage impressed between a voltage input terminal A and a voltage input terminal B. While the first group of switches Q1, Q2 are turned off by tuning off the third group of switches Q5, Q6, the second group of switches Q7, Q8 are turned on, so that voltage retained in the condenser C1 is generated between a voltage output terminal G and a voltage output terminal H.

The invention discloses a random forest-based non-invasive home appliance identification method, which aims to monitor a family internal power utilization condition without invading an interior of a family user, and is high in identification speed and high in accuracy. According to the adopted technical scheme, the method comprises the steps of establishing a load feature database; taking load features stored in the feature database as an original training set, and generating N training sub-sets in the original training set; combining N generated decision trees into a random forest; finishing a training process of the random forest through optimization of weights of different decision tree leaf nodes; detecting an electric appliance switching event by utilizing a secondary detection algorithm to obtain starting and ending time of event occurrence, and separating out current and voltage signals of a switched electric appliance from a bus signal, thereby obtaining the load features from separated data; and finally inputting the load features as input parameters to the trained random forest, and finishing electric appliance identification through voting.

An optical recording / reproducing apparatus having excellent resistance against vibration and noise is provided. In recording, coherent light is polarization-modulated with a spatial light modulator to generate signal light and reference light whose polarization directions are crossed at right angles with each other. The signal light permeates a polarizing beam splitter, and is incident to a quarter wavelength plate. The reference light passes through a passing hole, is diffused by a light diffuser and is incident to the quarter wavelength plate. The reference and signal light are converted into circularly polarized light which revolve in directions opposite to each other and condensed by a condenser lens, and then a predetermined area of an optical recording medium is irradiated with the reference and signal light. Thus, the reference and signal light are generated by modulating the incident light from the same light source and are coaxially incident to the polarizing beam splitter.

The invention discloses a rapid fingerprint identification method based on image characteristics and minutia characteristics. The method comprises the following steps: firstly, detecting a reference point and determining a direction thereof, and determining the reference direction of the reference point by observing the difference between the fingerprint direction and the radial direction in sector regions with different sizes; carrying out image characteristic extraction, performing feature selection after normalization, and finally, obtaining the characteristic vector of the fingerprint image; establishing a minutia template and transforming the obtained minutiae under a polar coordinate system to establish a fingerprint minutia template; and carrying out the characteristic matching, i.e. as for the input fingerprints to be compared, judging whether the two fingerprints are matched or nor by using the fingerprint image characteristics and the minutia template obtained from the three steps. The invention not only can effectively inhibit the influence generated during the fingerprint image translation and the rotation, but also avoids the dependence to the detected reference point and the direction thereof in the recognition process and can also rapidly and accurately judge whether the fingerprint to be identified is matched with the template fingerprint or not.

Disclosed is a blind restoration method for the motion blurred image; the steps are as follows: (1) the image is converted through the cepstrum method to figure out the blur extent and the blur direction of the blurred image; (2) the blur extent and the blur direction of the blurred image figured out in step (1), and the total variation (TV) method are adopted to process the restoration towards the blurred image. The method based on the total variation (TV) includes: the fixed-point iteration used as the outer-loop and the conjugate gradient method used as the inner-loop are adopted for loop iteration to obtain the restored image. The blind restoration method has the advantages of strong self-adaptation, strong anti-noise ability and good robustness; the blind restoration method has validity and practicality according to the processing effects of the simulation picture and the photographed picture.

A pneumatic tire including a sealant layer formed from a sealant fluid having adhesive properties that is provided on a tire inner circumferential surface corresponding with a tread portion; and a sound absorbing layer formed from a porous material that is provided via a barrier layer impermeable to the sealant fluid on an inner circumferential surface of the sealant layer; wherein a width W1 of the sound absorbing layer in a tire width direction is from 50 to 90% of a width W2 of the sealant layer in the tire width direction. The pneumatic tire has good puncturing seal property and noise preventing property.

A precision pulse detection system for time-of-flight sensors detects a zero axis crossing of a pulse after it crosses above and then falls below a threshold. Transmit and receive pulses flow through a common expanded-time receiver path to precision transmit and receive pulse detectors in a differential configuration. The detectors trigger on zero axis crossings that occur immediately after pulse lobes exceed and then drop below a threshold. Range errors caused by receiver variations cancel since transmit and receive pulses are affected equally. The system exhibits range measurement accuracies on the order of 1-picosecond without calibration even when used with transmitted pulse widths on the order of 500 picoseconds. The system can provide sub-millimeter accurate TDR, laser and radar sensors for measuring tank fill levels or for precision radiolocation systems including digital handwriting capture.

The invention discloses a pseudo-differential capacitive successive approximation register analog-digital converter. The analog-digital converter comprises a first capacitor array, a second capacitor array, a calibration capacitor array and a comparator, wherein lower-bit-segment sub-capacitor arrays of the first capacitor array keep single-end structures; a higher-bit first-segment sub-capacitor array of the first capacitor array and the second capacitor array construct a differential structure; and the first capacitor array and the second capacitor array construct a pseudo-differential capacitor array in which single ends are combined with the differential structure. In an analog-digital conversion process, a transition code value is formed after completion of a least-significant differential weight bit, thereby realizing differential-single end transition. An output end of the calibration capacitor array is connected with an output end of the second capacitor array through a coupling capacitor, and the calibration capacitor array is used for calibrating mismatch of capacitors in the pseudo-differential capacitor array and the offset of the comparator. Through adoption of the analog-digital converter, the chip area can be saved; self-calibration can be performed; and the conversion accuracy is increased.

The invention discloses a method and device for measuring the frequencies of high-frequency cosine signals under the undersampling rate, and relates to the field of digital signal processing. By combining the type of the zero crossing point with the distribution characteristic of apFFT phase spectrums, L spectrum position index values are selected from 2L peak value magnitude spectrum positions; according to the remainder selecting result, each apFFT phase spectrum is corrected through the all-phase ratio interpolation method so that the frequency of the apFFT phase spectrum can be estimated; the frequency estimation value obtained after each apFFT phase spectrum is corrected is used as a remainder, the remainders are processed according to the Chinese remainder theorem of the closed analysis form, and the frequencies of the original high-frequency signals are reconstituted through the frequency estimation values. According to the method and the device, the frequencies of the multiple paths of high-frequency cosine signals under the undersampling rate are measured, and the measuring range of the frequencies of the high-frequency signals is greatly widened; the novel spectrum correction method is adopted, and therefore the measuring accuracy of the frequencies of the high-frequency cosine signals is improved, and novel anti-noise performance of the high-frequency cosine signals under the low undersampling rate is ensured.

The invention relates to a method of range alignment in inverse synthetic aperture radar (ISAR) imaging, which is applicable to low signal-to-noise ratio data. The method directly corrects the target linear range walk by Keystone transformation, the transformation can be realized by linear interpolation, the computation amount is low, and the robustness is good under the low signal-to-noise ratio condition; as for the range walk problem of a quadratic term caused by target radial acceleration, firstly coherent accumulation of the adjacent range images is performed to obtain a high signal-to-noise ratio synthetic range image, and then an estimated value of the radial acceleration is searched to maximize the corrected kurtosis value of the quadratic sum of various range images after time delay adjustment; the radial acceleration search which takes the corrected kurtosis value as an index has overall significance, and the anti-noise performance is good. In the method, only one-dimensional search is needed instead of high-dimensional search, thus the computation amount is low.

The invention belongs to the technical field of sleep monitoring, and relates to a single-lead electroencephalography (EEG) automatic sleep staging method. The method comprises the following steps: (1) performing signal pre-processing; (2) extracting classification features; (3) carrying out sleep staging. The method provided by the invention has the advantages that 1, a pre-processing algorithm is designed to obtain single-lead EEG signals with better quality; 2, the method extracts multiple features from the time domain, the frequency domain and the nonlinear domain, and screens out the representative features; 3, a random forest model is adopted, so that over-fitting does not need to be worried about; the method has a good anti-noise ability, and the staging results of all decision trees can be obtained, so that the confidence probabilities of the random forest for all sleep stages are obtained; 4, a D-S evidence theory is combined, so that the accuracy rate of the sleep staging isfurther improved.

A precision pulse detection system for time-of-flight sensors detects a zero axis crossing of a pulse after it crosses above and then falls below a threshold. Transmit and receive pulses flow through a common expanded-time receiver path to precision transmit and receive pulse detectors in a differential configuration. The detectors trigger on zero axis crossings that occur immediately after pulse lobes exceed and then drop below a threshold. Range errors caused by receiver variations cancel since transmit and receive pulses are affected equally. The system exhibits range measurement accuracies on the order of 1-picosecond without calibration even when used with transmitted pulse widths on the order of 500 picoseconds. The system can provide sub-millimeter accurate TDR, laser and radar sensors for measuring tank fill levels or for precision radiolocation systems including digital handwriting capture.

The invention belongs to the technical field of remote sensing image processing and particularly relates to a hyperspectral image nonlinear abundance estimation method based on constrained least squares. According to the method, through introducing abundance nonnegative constraint, abundance sum-to-one constrain and the bounded constraint of a nonlinear parameter, a hyperspectral image nonlinear unmixing problem is transformed into a problem of solving the constraint nonlinear least squares of an abundance vector and the nonlinear parameter. Furthermore, an alternating iteration optimization algorithm is employed to solve the problem. According to the method, starting from a mixed model of a hyperspectral observation pixel, combined with abundance and nonlinear physics significances in the model, the shortcomings of linear unmixing are effectively overcome, and the method also has good anti noise performance and can be used as an effective solution of the hyperspectral remote sensing image nonlinear unmixing. The method has an important application value at the aspect of high precision unmixing based on a hyperspectral remote sensing image and the detection and identification of a ground target.

The invention discloses a high precision frequency measurement method and instrument at the under-sampling rate. The method includes the steps that spectrum correction is conducted through a triple-spectrum-line interpolation method, L pairs of frequency estimated values obtained after spectrum correction is obtained, and L pairs of phase information obtained after peak position correction is obtained; with the combination of the zero crossing point type and the L pairs of phase information obtained after correction, L frequency estimation values are picked out from the L pairs of frequency estimation values; all spectrum correction values and the L frequency estimation values are adopted as the remainder, and the frequency of an original high-frequency signal is reconstituted according to the Chinese remainder theorem in the closed analytical form. According to the measurement instrument, a single to be tested is subjected to the zero crossing point measurement processing firstly, and the original phase of the signal to be tested is determined; then sample sequences are obtained after analog / digital converter sampling with multi-path sampling frequency is conducted, the sample sequences enter a DSP device in the form of parallel digital input respectively, and frequency estimation of a high-frequency signal is obtained after internal processing is conducted through the DSP device; finally the frequency value is displayed with the help of an output driver and a display circuit of the output driver.

The invention discloses a random-forest-based circuit breaker mechanical fault diagnosis method and system. The method comprises: establishing a circuit breaker vibration sample database; respectivelyextracting time domain feature vectors of each vibration sample data in the circuit breaker vibration sample database, and combining the time domain feature vectors to obtain a feature vector; forming an original training sample set; collecting vibration signal data of a target circuit breaker, and preprocessing the data; extracting time domain feature vectors of vibration signal data of the target circuit breaker; combining the obtained time domain feature vectors into a feature vector F; and according to the obtained original training sample set and the feature vector F, using a random forest algorithm to perform fault diagnosis on the target circuit breaker. The method has the beneficial effects that the introduction of two kinds of randomness makes the random forest have good anti-noise ability, is especially suitable for fault diagnosis of circuit breakers, and can improve the accuracy of fault diagnosis.

The invention relates to a nonlinear un-mixing method of hyperspectral images based on kernel sparse nonnegative matrix decomposition. The nonlinear un-mixing method comprises the following steps: estimating the number of end members for hyperspectral images by utilizing a dimension virtual method; then, popularizing the conventional un-mixing algorithm based on a linear mixing model to a nonlinear characteristic space by utilizing a kernel method, and solving a nonlinear spectrum un-mixing problem by using an alternative iterative optimization method. The nonlinear un-mixing method of hyperspectral images based on kernel sparse nonnegative matrix decomposition has the beneficial effects that from a mixing model of hyperspectral observation pixels, the sparsity of the hyperspectral abundance is added into a sparse model, and the linear mixing model is mapped into a nonlinear mixing model by virtue of the kernel method, so that the defects of linear un-mixing are effectively overcome, and good noise resistances are simultaneously achieved, and therefore, the nonlinear un-mixing method can be used as an effective means for solving the un-mixing of hyperspectral remote sensing images.

A method for detecting a high impedance grounding fault based on fault resistance nonlinear identification comprises the steps: collecting phase voltages of a detected feeder line and an instantaneous value of a zero sequence current, respectively calculating a correlation coefficient of each phase voltage and the zero sequence current, if the correlation coefficient of one phase voltage and the zero sequence current is larger than a threshold value R, fitting a current voltage characteristic curve composed of the phase voltage and the zero sequence current in a sectional and linear mode through a least square method, accordingly, calculating and obtaining a coefficient, namely, a fault resistance nonlinear coefficient which can effectively present characteristics of the high impedance grounding fault according to the slope of each fitting straight line, judging whether a suspected high impedance grounding fault exists by comparing the fault resistance nonlinear coefficient and the threshold value, continuously detecting the lasting time of the suspected high impedance grounding fault, and if the lasting time exceeds delayed time, finally judging that the high impedance grounding fault occurs. Compared with a detecting method based on a harmonic wave, the method achieves high sensitivity, and compared with a method simply based on the time domain amount, the method achieves a better noise resisting capacity.

Circuits and methods are provided for transmitting a pseudo-differential output signal with relatively high immunity to noise and jitter. The output driver of the invention receives two differential input signals and outputs a single output signal with low voltage transistors and programmable impedance and on-die termination circuits. The pseudo-differential output driver consumes little circuit area and has low output capacitance.

The invention designs an image tracking method based on multi-neighborhood-aided two-dimensional ultrasonic deformed microstructure, which comprises the steps as follows: a two-dimensional ultrasonic cardiogram of a tested heart object is collected under a high frame frequency condition and used for offline analysis firstly; then any visible image is used as a selected initial frame of a region of interest (ROI) so that the ROI includes cardiac muscular tissues, simultaneously the interferences of grey scale signals is eliminated; after the ROI of the initial frame on an initial image I is completely selected, the original ROI is set as a center; moreover, the ROI and eight areas coating the surrounding of the original ROI and having same sizes are used as a new searching source region, the tracking vectors of all subregions with the sizes the same as the size of the original ROI in the searching area are traversed through an SAD (Sum of Absolute Differences) arithmetic; and weighted average is implemented on each tracking vector finally, thus obtaining the tracking result of the original ROI. Compared with the traditional SAD tracking method, the neighborhood tracking result of the ROI is sufficiently considered; therefore, the image tracking method based on multi-neighborhood-aided two-dimensional ultrasonic deformed microstructure has excellent noise immunity, and is especially beneficial for movement estimation and parameter calculation on movement issues.

In a pressure sensor which has a metal housing 12 containing a sensor chip 11 and a joint housing 14 and in which an insulating member 15 is arranged to electrically insulate both of the metal housing 12 and the joint housing 14 from each other, the metal housing 12 is connected to a stable potential such as, for example, a sensor power supply or a sensor ground. Thus, there can be solved a problem that the detection signal is liable to be influenced by electric noise from outside where a signal line of the pressure sensor and the sensor housing are electrically suspended or unfixed.

The invention discloses an edge computing terminal security level evaluation method for a random forest. The terminal security level evaluation method comprises the following steps: S1, setting security test items of a terminal and test results of the security test items; S2, testing the accessed intelligent terminal; S3, determining a corresponding relationship between the security level of the intelligent terminal and the single test result set; S4, calculating a security level corresponding to each edge terminal to obtain a data set; S5, dividing the data set into a training set and a testset; s6, inputting the training set into a random forest for training to obtain a mature classifier model; s7, inputting the test set into a random forest classifier model obtained through training, and comparing an obtained test result with the security level in the step S4 to obtain a standard classifier; and S8, evaluating the security level of the newly accessed terminal by using the standardclassifier model. According to the method, the data security requirements of the edge terminal are divided according to the grades, and edge computing side terminal security assessment can be carriedout through a quantized objective standard according to confronted security risks and system complexity.

The invention provides a method and a system for adjustment of voice control accuracy. The method is implemented by the following steps: selecting a specific neural network model, and initializing network weights; monitoring whether there is user voice control signal input; pretreating an input signal; sending the signal into the well-trained neural network after feature extraction so as to obtaina classified recognition result; judging whether the recognition result matches a voice control instruction pre-stored in the system; executing a corresponding control operation if the recognition result matches the voice control instruction; calculating the voice control accuracy if the recognition result doesn't match the voice control instruction; letting the system enter an accuracy regulation mode when the voice control accuracy is lower than a predetermined value or a user initiates the adjustment process; and retraining the network model until the accuracy is higher than the set value.The model can be trained in real time according to needs, the voice control accuracy is adjusted, and reliability of controlling a controlled plant is improved; and by using the improved neural network model, the voice recognition accuracy is raised.

The invention discloses a gas source positioning technology in a wireless sensor network without measuring wind speed and wind direction. The technology includes the following steps: detecting gas concentrations through the wireless sensor network; adopting a plume model which is based on the turbulent diffusion theory to obtain a gas concentration expression formula; conducting sum of square of deviation on the concentrations which are obtained from the detection by sensors to obtain a required object function, the error sum of squares of the measuring value of the sensor and an actual value serving as the object function; using the particle swarm optimization algorithm to resolve the object function to obtain a positioning result and environment information. According to the invention, the technology conducts online estimation on the wind speed and wind direction without adding detection means, and increases robustness and accuracy of gas source positioning.

The invention discloses a space-time continuous PM2.5 inversion method. The method comprises the steps of establishing a random forest regression model , wherein meteorological dynamic indexes of an inversion area and a satellite AOD serve as interpretation variables to be input into a random forest network, then training the random forest regression model to obtain an optimal model, and conducting inversion under the optimal model to obtain a PM2.5 concentration satellite estimation value; Determining a root-mean-square error of the PM2.5 concentration satellite estimation value; Calculatinga spatial interpolation observed by each station by using a common Kriging interpolation algorithm; Determining a root-mean-square error of the spatial interpolation; And using an inverse variance weighting method to fuse the PM2.5 concentration satellite estimation value and the spatial interpolation to obtain a final PM2.5 concentration inversion value. According to the method, the influence ofmultiple collinearity on an inversion result is overcome, the good noise resistance is achieved, seamless estimation of the near-surface PM2.5 concentration is achieved, and data support is provided for real-time continuous air quality monitoring of an area.

The invention provides an extraction method for facial expression feature. The method comprises the steps that a facial expression image is divided into N blocks of images, and the size of each branch image is m * n; the coded value of LWBP 1 and LWBP 2 of all pixels in each image are calculated by a locally weighted binary pattern namely LWBP; the LWBP column diagram of each image is counted; two column diagrams of each image are directly overlapped to get a column diagram to serve as the final LWBP feature of each image; all the statistical histograms of all blocks of the images are connected in sequence to obtain a LWBP feature vector, used for classification and identification, of the whole image. By calculating weighting gray values of two-group symmetrical eight templates respectively, the size of the weighted values and equal weighted values in every direction are compared and coding is conduced, the gray level change of neighborhood pixels in different directions are considered comprehensively, the detail feature of the facial expression can be effectively represented, certain robustness is possessed for noise, the identification speed is quickened obviously, and the practicality is possessed.