80 results about "Periodogram" patented technology

A sensor assembly for sensors such as microfabricated resonant sensors is disclosed. The disclosed assembly provides improved performance of the sensors by providing a thermally insensitive environment and short pathways for signals to travel to processing components. Further, the assembly provide modular construction for the sensors and housing modules, thereby allowing replacement of the sensors at a lower cost. The assembly includes a sensor module including a sensor formed on a conductive substrate with a cavity formed on one surface. The substrate has conductive vias extending from the cavity to a second surface of the substrate. A housing assembly accommodates the sensor and includes a rigid housing, preferably made from a ceramic. An electronic component, such as an amplifier, is mounted on the rigid housing. The electronic component electrically engages the vias substantially at the second surface of the substrate. The electronic component receive signals from the sensor through the vias. The signals are then processed through an amplifier and a digital signal processor using a modified periodogram.

The invention provides a method and device for analyzing the acceleration response of rail vehicles. The method comprises the following steps: a. acquiring acceleration response signals of the rail vehicles and the corresponding speed information thereof; b. grouping the acceleration signals according to speeds; c. obtaining a power spectrum or a power equivalent amplitude spectrum of the corresponding acceleration response signal of each speed stage by a periodogram method; d. representing the result of step c by a three-dimensional speed-frequency spectrogram; and e. identifying local peak values not changing with speed and / or local peak values changing with speed in the three-dimensional speed-frequency spectrogram. The method and the device for analyzing the acceleration response of the rail vehicles of the embodiment of the invention can comprehensively, visually and effectively obtain the characteristics of the rail vehicles and input of fixed wavelength vehicles.

The invention discloses an orthogonal frequency division multiplexing (OFDM) frequency domain interpolation pilot frequency-based cyclostationary feature spectrum sensing method. The invention mainly aims to solve the problems that the performance of the traditional sensing technology is limited by the length of a cyclic prefix, and the performance is lowered by the random variation of a pilot frequency phase. The OFDM frequency domain interpolation pilot frequency-based cyclostationary feature spectrum sensing method comprises the following implementation steps of (1) transforming a time domain signal into a frequency domain signal by performing fast Fourier transformation on the time domain signal received by a receiving end; (2) calculating a spectral correlation function of the frequency domain signal by utilizing a time domain smoothness periodogram method; (3) selecting feature points from the spectral correlation function; (4) constructing corresponding test statistics by utilizing the selected feature points according to the channel condition; and (5) comparing the test statistics with corresponding sensing judgment thresholds so as to judge whether a master user signal exists in a channel to be sensed or not, and giving the reliability tolerance of the master user signal. The OFDM frequency domain interpolation pilot frequency-based cyclostationary feature spectrum sensing method disclosed by the invention does not depend on the length of the OFDM symbol cyclic prefix, is good in detection performance under the low-signal to noise ratio fading channel condition, and can be widely applied to various broadband wireless OFDM communication systems.

The invention provides a periodic detection method and system for a GNSS observation station coordinate time sequence. The method comprises the steps of acquiring a GPS observation station coordinatetime sequence observed value, removing gross errors and correcting an antenna phase center deviation; performing preliminary spectrum analysis on the GPS observation station coordinate time sequence by using a periodogram method; acquiring a plurality of major cycle frequencies of a corresponding observation station, and sorting according to the amplitudes of main frequencies; describing the GPS observation station coordinate time sequence by using a harmonic function, acquiring a harmonic function model of the GPS observation station coordinate time sequence, and building a harmonic functionmodel matrix; using the main frequencies as prior constraints, and acquiring the standby frequencies of a plurality of periodic signals; resolving the harmonic function model based on a least squarescriterion, acquiring optimal frequencies and verifying the standby frequencies by using a hypothesis testing method, and building the harmonic function model including the plurality of optimal frequencies; and according to the standby frequency after hypothesis testing is performed, resolving the harmonic function model matrix based on the least squares criterion, and acquiring a detection resultof any GNSS observation station periodic signal.

The invention discloses a signal-to-noise ration estimating method of time frequency overlapping signals under a frequency spectrum sharing mode. According to the method, a code element rate of time frequency overlapping signals is estimated according to a cyclic frequency corresponding to a discrete spectral line of an amplitude spectrum of a generalized fourth-order cyclic cumulant of receiving signals; power of each component signal and a power sum of the component signals are estimated; a frequency band scope of the receiving signals is estimated, and total power of the receiving signals is obtained by estimating a power spectrum of the receiving signals by use of a multi-window periodogram method; and noise power of the time frequency overlapping signals is calculated, and accordingly, a signal-to-noise ratio of the time frequency overlapping signals under the underlay frequency spectrum sharing mode is estimated. According to the invention, under the conditions of a low noise-to-signal ratio and a high frequency spectrum overlapping rate, the estimation performance for the signal-to-noise ratio of the time frequency overlapping signals under the underlay frequency spectrum sharing mode is excellent.

A method for studying muscle fatigue on the basis of static myoelectricity after electrical stimulation includes respectively acquiring static surface myoelectric signals of each subject: selecting the subjects, arranging experimental periods, placing surface myoelectric electrodes and stimulating electrodes on the subjects, and acquiring the static surface myoelectric signals; and respectively analyzing power spectrums of the acquired static surface myoelectric signals: computing the acquired static surface myoelectric signals by a periodic diagram process to acquire the power spectrums, drawing frequency spectrograms according to the power spectrums, computing median frequencies and analyzing the median frequencies. The method has the advantages that change of the surface myoelectric signals after electrical stimulation can be represented, myoelectric response caused by electrical stimulation can be comprehensively evaluated in a frequency domain, an experimental basis is provided for follow-up study, accordingly, an idea is provided for technical standards for evaluating effects of electrical stimulation on human bodies, and development of electrical stimulation is promoted.

Signal processing technology for assessing dynamic system similarity for fault detection and other applications is based on time- and frequency-domain time series analysis techniques and compares the entire autocorrelation structure of a test and reference signal series. The test and reference signals are first subjected to similar pre-processing to help guarantee signal stationarity. Pre-processing may include formation of multivariate signal clusters, filtering and sampling. Multivariate periodograms or autocovariance functions are then calculated for each signal series. Test statistics are computed and assessed to determine the equality of the test and reference signals. When the difference between sample autocovariance functions or periodograms of such signals exceeds a preselected threshold value, fault detection signals and / or related diagnostic information are provided as output to a user.

The invention relates to a method and a device for detecting respiration signals. The method comprises the following steps: original signals are collected; filter processing is conducted on the original signals, and filtering parameters adopted in filter processing are confirmed according to a harmonic structure of slow time domain respiration signals by analyzing in advance; a periodogram of slow time domain signals of the original signals is calculated after the filter processing; noise power of the slow time domain signals of the original signals is estimated after the filter processing; a harmonic graph is calculated according to the harmonic structure of the slow time domain respiration signals, the periodogram of the slow time domain signals and the noise power of the slow time domain signals; and whether the harmonic graph is larger than a preset threshold or not is judged, if the harmonic graph is larger than the preset threshold, the respiration signals exist, and if the harmonic graph is not larger than the preset threshold, the respiration signals do not exist. According to the method and the device for detecting the respiration signals, the filtering parameters are confirmed by adopting the harmonic structure of the respiration signals so that the filter processing is conducted, environmental noise can be filtered well, the respiration signals can be reserved as much as possible, and detecting performance is improved.

The invention provides a method for predicting network traffic and a prediction algorithm. The method, which compensates for the time-delay effect by continuously carrying out the time sliding on prediction sequences, comprises the following steps: Step 1, extracting a sample array from real traffic sequences, designating the sample array as FArray and initiating the values of three variables, M, N and m; Step 2, calculating the self-similarity index H of the sample array FArray on the basis of methods, such as periodogram, R / S analysis, wavelet analysis and the like; Step 3, estimating the order of the sample array by the AIC (Akaike Information Criterion), wherein, AIC(n,m) = lnsa + 2(n+m+1) / N (1), and determining that the order of the model is (p,q), if AIC(p,q) = min AIC(n,m); Step 4, calculating the model parameter ARMA [phi, theta], wherein, ARMA [phi, theta] = ARMA (pbest, qbest), and the calculating method comprises the following steps: (1) estimating the parameter of the autoregression part, and (2) estimating the average sliding coefficient; Step 5, calculating the coefficient vector, pij = theta1pij-1+ theta2pij-2+lambada+thetaqpij-q+phij(j>0), wherein, pi0 is equal to negative 1, and when j is larger than the sum of p and d, phij is equal to 0; and Step 6, predicting the network traffic according to the following formula: X(h) = *pij[(h)]X[t+h-j].

The invention discloses a whole car quality estimating method based on a frequency response characteristic. The whole car quality estimating method is suitable for real-time monitoring of the whole car quality in the process of constant speed running of a car. The whole car quality estimating method establishes an expression which can manifest the relationship between the longitudinal accelerated speed of the whole car and the frequency response characteristic between wheel speeds, and whole car quality estimating is further achieved on the basis of the expression. The estimating method comprises the following steps that the accelerated speed and wheel speed signals are correspondingly collected firstly; then by using a periodogram method, the amplitude ratio of two signals under different frequency is obtained; and finally, by using combining and recurring a least square method smoothing, estimating values of the whole car quality are obtained. The whole car quality estimating method based on the frequency response characteristic has the advantages that by only adopting the accelerated speed and the wheel speed signals, tyre longitudinal force information is not needed, and the method is applied conveniently; and estimating is achieved by adopting frequency-domain information, and the method has the characteristics that the method is not sensitive to wheel speed noise and errors.

The invention relates to a highway background identifying and highway background inhibiting method of a traffic radar based on millimeter wave, realizes the power spectrum automatic identification and the real-time update of highway background by utilizing traffic radar echo signals containing vehicle information and background information simultaneously, and accomplishes the inhibition of the highway background. The method takes the time domain digital echo signals of the lateral millimeter wave traffic radar as signal input, and obtains the time sequence of a radar echo power spectrum which is changed along with time by applying a periodogram method; the time sequence of the power spectrum is arranged in an ascending order according to the range of the power spectrum at each frequency point; the sequence of an ordered power spectrum with partial range is selected as effective data estimated by the power spectrum of the highway background; coherent average is performed to the sequence of the ordered power spectrum with effective range; the real-time update of the power spectrum of the highway background is realized by utilizing a self-learning method; and the highway background is inhibited. The methods can accurately identify the power spectrum of the highway background on a real-time basis, and can well inhibit the highway background, thereby greatly improving the signal-to-noise ratio of the radar echo signals.

The invention discloses a road network traffic flow space-time prediction method for intelligent traffic and intelligent driving. The method comprises the steps of obtaining, encoding, decoding and predicting, and therefore the traffic flow of a highway network within the predicted period of time is obtained according to predicted picture signals. On one hand, due to the fact that a reverse toothshaped diffusion convolution circulation module is constructed in the encoding step and the decoding step separately, a state variable is reserved in a convolution layer, the maintained state variablenumber is decreased, in the convolution diffusion process from reverse tooth shaped circulation to the optimal state variable, two-time state updating operation can be performed at the same moment inthe reconstructed diffusion convolution circulation processing process, and the time short-term dependency can be enhanced; on the other hand, due to the fact that in the encoding and decoding steps,day periodogram signals and week periodogram signals are adopted as considering factors for decoding processing, basis information is not single, noise possibly introduced in the accumulative learning process can be effectively restrained, and therefore the prediction accuracy of predicted picture signs is improved.

A method for detecting the presence of a transmission signal in a wireless spectrum channel. The frequency of a signal is converted from a first frequency to a second frequency. The signal with the second frequency is filtered to remove signals that are not within the band of the second frequency. An averaged periodogram of the signal is calculated. A value of the averaged periodogram is comparedto a threshold. The presence of the transmission signal is detected, if the value of the averaged periodogram exceeds the threshold.

The invention relates to a spectrum correlation characteristics-based frequency spectrum detection method in a cognitive radio system. Spectrum estimation is performed on a transmitted signal of a master user transmitter and a received signal of a cognitive user receiver by using a minimum variance distortionless response (MVDR) algorithm; spectrum related quantities of MVDR spectrums of the transmitted signal and the received signal are taken as detection statistical quantities; a threshold meeting a false alarm probability condition is solved; and the detection statistical quantities are compared with the threshold to judge whether the frequency spectrum is occupied. The method is implemented by the following five parts of: calculating the MVDR spectrum of a sampling signal of the transmitted signal; calculating the MVDR spectrum of the sampling signal of the received signal; calculating detection statistical quantities; calculating a threshold value th meeting the false alarm probability Pf; and judging whether the frequency spectrum is occupied. By the spectrum correlation characteristics-based frequency spectrum detection method, the requirements of an institute of electrical and electronics engineers (IEEE802.22) standard on a detection time can be met, simultaneously, the resolution for performing the spectrum estimation is higher and the spectrum frequency detection performance is higher compared with the conventional correlation detection algorithm for performing spectrum estimation by a periodic diagram method.

A periodogram method based punch press noise power spectrum estimation improvement method includes initializing a power spectrum detection device, and setting a sensor sampling frequency, a discrete Fourier transform parameter, a window function shape, window function length, an iteration counter i initial value, a total iteration time S, and an initial value of an average discrete Fourier transform approximate value; using a punch press blanking control signal as a starting sampling trigger signal; using a punch press retrieve hydraulic hammer control signal as a finishing sampling trigger signal; waiting for the trigger signal, wherein a trigger sensor finishes collecting a blanking noises x(t) sample; windowing the collected noise sample; using an iterative method to calculate a discrete Fourier transform average value of an L point, and storing the result of the discrete Fourier transform average value; repeating the steps until the iteration counter i=S; dividing a square of the discrete Fourier transform average value by data length to obtain a power spectrum estimation value.

An information processing apparatus is described. This determines a physiological parameter of an individual, the apparatus comprising: image circuitry configured to obtain a series of images of a skin exposed region of the individual; and processing circuitry configured to perform a periodogram on at least one of the red, green and blue channels of the skin exposed region of the series of images to obtain frequency components of the channel; and to determine the physiological parameter based on the periodogram.

The invention provides a wireless microphone signal detection method based on a periodogram, which is used for solving the problem of incapability of distinguishing narrow band interference from a wireless microphone signal in the conventional detection method. The method comprises the following steps of: acquiring a time-domain digital signal needed by detection through an antenna module, a radio-frequency front-end module, an analog to digital conversion module and a time-domain signal preprocessing module; finishing detection of a microphone signal in a frequency domain, i.e., computing to obtain the average value of periodograms of M segments of time-domain digital signals to be detected, performing displacement processing on the average value to obtain displacement vectors, estimating the average value and a covariance matrix of the displacement vectors, finding a maximum value point in the displacement vectors, and selecting a plurality of points from the left and right of the maximum value point serving as a center to constitute an information vector; computing the information vector by using a decision theory to obtain a decision statistic; and simulating or computing a threshold value through a preset method, determining as a narrow band interference if the statistic is smaller than the threshold value according to judgment, otherwise, determining as a wireless microphone signal.

In accordance with the present invention, a method for obtaining frequency information about a given data set is realized. The method comprises the steps of providing a processing unit; inputting a raw data set into the processing unit; optionally removing at least one trend from the raw data; ordering the raw data; estimating power spectral density using an eigenanalysis approach and the inputted raw data and the ordered raw data; simultaneously estimating the power spectral density using the raw data and a periodogram; generating a time-series representation of the raw data to which curve fitting is applied; comparing the results from the power spectral density estimating steps and the time-series representation generating step to determine if any frequencies suggested by the eigenanalysis approach estimating step are valid; and generating an output signal representative of each valid frequency.

A method and an apparatus of estimating a frequency offset in a wireless communication system are provided. An orthogonal frequency division multiplexing (OFDM) receiver performs envelope equalized processing (EEP) with respect to a reception signal and calculates a partial periodogram with a plurality of test values based on the reception signal which goes through the EEP. The OFDM receiver estimates a first frequency offset, a second frequency offset, and a third frequency offset based on two partial periodograms adjacent to each other among the partial periodograms for the plurality of test values.

The invention provides a decoding method for selected call signals of a segment handling airborne selective calling system. The decoding method is small in calculated quantity, precise in estimated value and capable of reducing erroneous judgment and missed judgment probabilities. According to the technical scheme, the method includes the steps that a signal acquisition module carries out windowing modulation on acquired single-frame signals through a signal preprocessing module, framing processing is conducted on the selected call signals, a power spectrum of each single-frame signal and a power spectrum of each windowing modulation signal are estimated by means of a periodogram method through a power spectrum estimation module, and coarse estimated values are obtained; frequency power spectrum estimated values and amplitude estimated values nearby the reference frequency of the selected call signals are corrected through an energy center correction module according to estimated results to obtain high-precision frequency estimated values and high-precision amplitude estimated values, a state judgment module synthesizes frame results and conducts state judgment through the precise estimated values, a skip module synthesizes judgment results of frames through a decoding state machine, and accordingly the whole decoding process is completed.

The invention belongs to the technical field of inverse synthetic aperture radar imaging, and particularly discloses a GNIAA-based ship target ISAR imaging method. The method comprises the following steps: initializing echo data subjected to motion compensation, obtaining a spectrum estimation initial value by using a periodogram, updating a covariance matrix of a signal to obtain a weighting matrix, on this basis, obtaining an updated value of spectrum estimation by using WLS, then iterating the process for multiple times, and taking a spectrum estimation result after iteration as an estimation result of the current distance unit; and finally, traversing a distance unit where the target is located to obtain a high-resolution ISAR image of a ship target. According to the method, the influence of noise on the spectrum estimation process is comprehensively considered, so that the final estimation result is more accurate.

A method of analyzing a spectrum of one-dimensional or multi-dimensional signal X(t) requires a number of steps including deriving coefficients [AN(ω), BN(ω)] of an Lp-norm harmonic regression of tie signal with 0<p≦∞ and pγ2, squaring the coefficients, summing the squared coefficients, and scaling the summed, squared coefficients with a constant c to realize a periodogram of X(t) as LN(ω)=c{[AN(ω)]+[BN(ω)]2}. The method may include receiving the signal X(t), storing the received signal X(t), and outputting the periodogram LN(ω). The method may still further include scanning to maximize the periodogram LN(ω) by identifying its largest peak(s) and comparing the amplitude of the identified largest peak(s) with a threshold to determine if the largest peak(s) is(are) attributable to a presence of a periodic signal. The coefficients are preferable derived from a time series signal X(t), t=1, 2, . . . , N, but may include receiving a continuous-time signal and converting it to the time series signal.

Disclosed are an apparatus and a method for normally receiving data by accurately estimating and compensating for a frequency offset for a wireless frequency channel through which data are transmitted in a communication system under wireless frequency environment. In the present invention, data transmitted through the wireless frequency channel are received, the frequency offset in the wireless frequency channel from the receive data is estimated based on an interpolation scheme using the periodogram, and the frequency offset is compensated to receive the data by frequency-synchronizing with the wireless frequency channel.

The invention discloses a marine target detection method based on the power spectrum box dimension, and belongs to the technical field of radar signal processing. The method includes obtaining a timesequence X of sea clutter echoes, and adopting a periodogram method to calculate a power spectrum S(f) of the sea clutter echoes to obtain a power spectrum sequence S of the sea clutter echoes; performing maximum value normalization processing on the power spectrum sequence S to obtain a normalized power spectrum sequence Su; and setting the grid size delta of the box dimension, calculating the box dimension D of the power spectrum sequence, using the box dimension D as statistics inspection amount to design a nonparametric constant false alarm detector, and completing radar target detection.Detection performance of the method is better than a statistical model-based detection algorithm and an existing time domain fractal dimension detection algorithm, and improves detection performance of a marine target under a low signal to clutter ratio condition.