109 results about "Discrete time domain" patented technology

Methods and apparatus for signal processing are disclosed. A discrete time domain input signal x_m(t) may be produced from an array of microphones M₀ . . . M_M. A listening direction may be determined for the microphone array. The listening direction is used in a semi-blind source separation to select the finite impulse response filter coefficients b₀, b₁ . . . , b_N to separate out different sound sources from input signal x_m(t). One or more fractional delays may optionally be applied to selected input signals x_m(t) other than an input signal x₀(t) from a reference microphone M₀. Each fractional delay may be selected to optimize a signal to noise ratio of a discrete time domain output signal y(t) from the microphone array. The fractional delays may be selected to such that a signal from the reference microphone M₀ is first in time relative to signals from the other microphone(s) of the array. A fractional time delay Δ may optionally be introduced into an output signal y(t) so that: y(t+Δ)=x(t+Δ)*b₀+x(t−1+Δ)*b₁+x(t−2+Δ)*b₂+ . . . +x(t−N+Δ)b_N, where Δ is between zero and ±1.

The invention discloses a clustering-based blind source separation method for synchronous orthogonal frequency hopping signals. The method comprises the following steps of: acquiring M sampled paths of discrete time-domain mixed signals; obtaining M time-frequency domain matrixes of the mixed signals; preprocessing the time-frequency domain matrixes of the frequency hopping mixed signals; estimating frequency hopping moments, normalized mixed matrix column vectors and frequency hopping frequency; estimating time-frequency domain frequency hopping source signals by utilizing the estimated normalized mixed matrix column vectors; splicing the time-frequency domain frequency hopping source signals between different frequency hopping points; and recovering time-domain source signals according to time-frequency domain estimate values of the source signals. According to the method, the frequency hopping source signals are estimated only according to the received mixed signals of a plurality of frequency hopping signals under the condition of unknown channel information, and the frequency hopping signals can be subjected to blind estimation under the condition that the number of receiving antennae is smaller than that of the source signals; short-time Fourier transform is utilized, so that the method is low in computation amount; and the frequency hopping signals are subjected to blind separation, and meanwhile, a part of parameters can also be estimated, so that the method is high in practicability.

Several techniques are disclosed for isolating either heart or breath rate data from a photoplethysmograph, which is a time domain signal such as from a pulse oximeter. The techniques involve the use of filtering in the frequency domain, after a Fast Fourier Transform (FFT) has been conducted on a given photoplethysmograph also references as a given set of discrete time-domain data. The filtering may be applied to an identified fundamental frequency and one or more harmonics for heart related parameters. The filter may be truncated to the frequency data set and further applied multiple times to improve roll off. After filtering, an Inverse FFT (IFFT) is used to reconstruct the time-domain signal, except with undesirable frequency content eliminated or reduced. Calculation or measurement of parameters is then conducted on this reconstructed time-domain signal.

A tracking device may include a body, a sound emitter operable to emit a sound, an array of two or more microphones adapted to produce discrete time domain input signals at a runtime, one or more processors coupled to the array of two or more microphones; and a memory coupled to the microphones and the processor. The memory has a set of processor readable instructions embodied therein. The instructions include one or more instructions for:

determining a listening direction of the sound source relative to the microphone array from the discrete time domain input signals; using the listening direction in a semi-blind source separation to select filtering functions that separate out sounds from the sound emitter from the discrete time domain input signals; identifying a listening zone containing the sound emitter from the filtering functions; and determining a location of the sound emitter from the identified listening zone.

Several techniques are disclosed for isolating either heart or breath rate data from a photoplethysmograph, which is a time domain signal such as from a pulse oximeter. The techniques involve the use of filtering in the frequency domain, after a Fast Fourier Transform (FFT) has been conducted on a given photoplethysmograph also references as a given set of discrete time-domain data. The filtering may be applied to an identified fundamental frequency and one or more harmonics for heart related parameters. The filter may be truncated to the frequency data set and further applied multiple times to improve roll off. After filtering, an Inverse FFT (IFFT) is used to reconstruct the time-domain signal, except with undesirable frequency content eliminated or reduced. Calculation or measurement of parameters is then conducted on this reconstructed time-domain signal.

The invention discloses a power line communication system impulse noise suppression method based on L1/2 norm regularization. At a sending end, discrete time domain signals with cyclic prefixes is transmitted to a receiving end through a channel; at the receiving end, based on a compressed sensing theory, through introduction of regularization parameters and utilization of an iteration solving method, first the problem of estimation of impulse noise is converted into the problem of regularization of an L1/2 norm minimum value of the impulse noise, then the problem is converted into a form containing a two-step iteration result and the iteration solving method is utilized for solution, and thus estimation of an amplitude point of the impulse noise is relatively accurate; and by adoption of a threshold function to process the iterative result, a sampling point which is not affected by impulse noise interference has a relatively small estimation error.

The invention discloses a gearbox fault detection method based on flexible time-domain averaging. The gearbox fault detection method comprises the steps of: 1, adsorbing an acceleration transducer on a bearing end cover of a gearbox to be detected; 2, acquiring vibration signals of the gearbox through data acquisition equipment to solve a frequency-domain discrete sampling value of the vibration signals; 3, calculating a continuous time expression of time-domain averaging; 4, converting the continuous time expression into a trigonometric function expansion form; 5, weighting ak to realize filtering, de-noising and order information extracting for the time-domain averaging; 6, carrying out discrete sampling to obtain average sequences of discrete time domains; and 7, observing periodical impacts occurring in the sequences obtained in 6, and judging the type and the severity of a gearbox fault. According to the invention, truncation errors are inhibited effectively, and the advantages of increasing the resolution ratio of the signals and increasing the detection efficiency for the gearbox are achieved while a de-noising effect is achieved.

The invention discloses a cognitive radio frequency spectrum sensing method based on multi-antenna Friedman inspection. The cognition radio frequency spectrum sensing method includes receiving radiofrequency signals with continuous time domains by a plurality of receiving antennas; carrying out down-conversion and time-domain sampling processing for the radiofrequency signals with the continuous time domains to obtain base-band signals with discrete time domains; carrying out modular operation for the base-band signals with the discrete time domains at first, and then squaring operational results to obtain instantaneous powers; comparing the instantaneous powers of the different antennas at the sampling moment in the same time domain by a Friedman inspection method; assigning numbers sequentially ranging from 1 to M to comparison results from small to large; computing a Friedman inspection statistical magnitude; and finally comparing the Friedman inspection statistical magnitude with a judgment threshold to judge whether other wireless communication services occupy a frequency band or not. Accordingly, a frequency spectrum is sensed, and a sensing performance is good. By the aid of the cognitive radio frequency spectrum sensing method, the shortcoming that noise power needs to be accurately foreseen in an existing energy detection method is overcome, and the shortcoming that frequency spectrum sensing is failed when time domain relevancy is low or time domains are irrelevant among received signals of multiple antennas in a covariance matrix detection method is also overcome.

The invention belongs to the technical field of wireless communication, and particularly relates to a method for realizing the phase noise estimation by an iteration method in a wireless communication system. According to the method, firstly, the equivalent discrete time domain channel impulse response is estimated through channel estimation sequences, then, a CPE (common phase error) of the phase noise is estimated through interpolation, and finally, the phase noise estimation is realized by the iteration method, so the phase noise is compensated, the reliability of the system is improved, and the bit error rate is reduced.

Methods and apparatus of channel estimation using time-domain parameter extraction are disclosed. The wireless channel can be modeled by a multipath model with a limited number of parameters in the continuous time domain. In the discrete time domain, the multipath model leads to channel impulse responses that have a limited number of channel taps with non-negligible energy. Extracting the time-domain parameters and then reconstructing the channel yields channel estimates that have better accuracy. Time-domain parameter extraction also has lower computational complexity than existing methods.

The invention relates to a method for representing a residual stress of a film. The method comprises that a sample wafer of a film/substrate structure is used, a laser is controlled to emit a burst-pulse laser beam of certain frequency and energy, a linear laser beam is gathered in the surface of the sample wafer, and the surface of the sample wafer generates surface supersonic waves; a piezoelectric transducer carries out detection and collects discrete time-domain voltage signals; an experimental dispersion curve is obtained; modeling is carried out, and a theoretical dispersion curve of a film/substrate model in a residual-stress-free state is obtained; and the experimental dispersion curve is compared with the theoretical dispersion curve, a residual stress magnitude sequence of films of sample wafers is determined qualitatively. The residual stress of the film can be detected rapidly and losslessly.

The invention discloses a frequency spectrum sensing method based on multi-antenna instantaneous power. According to the method, multiple antennas are utilized to receive continuous time domain radio-frequency signals; downconversion and time domain sampling are performed on each continuous time domain radio-frequency signal then, and then discrete time domain baseband signals are obtained; values of instantaneous power of time domain sampling points in each discrete time domain baseband signal at each time domain sampling time are then calculated; test statistics are calculated by using ranking and deassign results of instantaneous power of the multiple time domain sampling points at the same time domain sampling time and ranking and deassign results of power difference values between the maximum value of the instantaneous power and the minimum value of the instantaneous power; and, finally through comparison of the test statistics with a judgment threshold, whether other wireless communication services occupy a frequency band is determined, and frequency spectrum sensing is achieved. The method has the advantage of good frequency spectrum sensing performance, overcomes the defect that an energy detection method needs to know noise power, and also overcomes the defect that a characteristic value detection value has low correlation between the received signals or poor frequency spectrum sensing performance while the received signals are uncorrelated.

The invention discloses an optical pulse signal simulation generation method influenced by atmospheric turbulence and belongs to the technical field of wireless optical communication of atmospheric channels. The optical pulse signal simulation generation method comprises the following steps: firstly calculating a series of optical pulse discrete time domain waveform data arriving at a receiver by using a multi-random-phase-screen-based optical pulse atmospheric turbulence transmission value simulation method and saving the series of optical pulse discrete time domain waveform data in a computer file; then generating modulation control signals of an electro-optic intensity modulator by a control computer according to the discrete time domain waveform data in the computer file and modulating laser signal intensity so as to simulate and generate the optical pulse signals. Compared with the existing semi-object simulation method, the method is not limited by the physical conditions of transmission distance and atmospheric turbulence parameters; the method is relatively high in flexibility and applicability.

The invention relates to an oil pumping device indicator diagram dynamic identification method and device based on a BP neural network. The method comprises the steps of characteristic database establishing and dynamic identification. An establishing process comprises the steps that time domain data of an oil pumping device indicator diagram sample are normalized and sampled to acquire a discrete time domain data sequence; Fourier transformation is carried out on the time domain data sequence to acquire a frequency domain data sequence; partial data in the frequency domain data sequence are used to replace partial data in the time domain data sequence, and a Fourier approximation characteristic value is acquired; the normalized oil pumping device indicator diagram sample is divided into four parts, and a characteristic vector is extracted; the Fourier approximation characteristic value and the characteristic vector are stored in a characteristic database; and a BP neural network algorithm is used to train the oil pumping device indicator diagram sample, so as to correct the Fourier approximation characteristic value in the database. According to the invention, the automation management level of an oil pumping device is enhanced; the work efficiency in an oil field is improved; and the management system of oil well operation is improved.

The invention discloses a magnetic suspension shaft system falling track recognition and resuspension control method and device, and belongs to the technical field of magnetic suspension bearings. The method includes the steps: calculating the sampling period of shaft system displacement signals; monitoring the suspension state of a shaft system; acquiring discrete time domain displacement signals of the shaft system; acquiring instantaneous frequency spectrum signals by Hilbert transformation; comparing expected values of radial displacement signals of the shaft system within the sampling period and expected values of instantaneous frequency of shaft system displacement with threshold values, determining track response of the shaft system and further proposing corresponding control strategies. When all-round friction happens, the swirl frequency of the shaft system can be effectively reduced, damage to the magnetic suspension bearings is reduced, resuspension of the shaft system is realized, vibration energy of the shaft system can be reduced when high-frequency swing happens, and the shaft system is effectively protected. According to the method, movement track response of the shaft system is judged only by displacement signals of the shaft system, the signals are easily acquired, and instantaneity, simplicity and convenience are simultaneously achieved.

The invention discloses a sampling frequency selection method of a wind turbine hydraulic pitch change system. The method comprises the following steps: 1) the vulnerability of an analog system to be digitally processed is verified by combining with a mechanism model of a wind turbine hydraulic pitch change servo system through a continuous time analog domain magnitude-frequency characteristic analysis method to guarantee the effectiveness of subsequent digital system stability design; 2) a system discrete time frequency domain analysis model is built based on a sampling frequency 1/T according to the system digital z conversion and the bilinear w conversion; 3) an optimal sampling frequency section is obtained by a MATLAB tool according to an optimal vulnerability phase margin section and the system discrete time frequency domain analysis model; and 4) top and bottom limitations of the obtained optimal sampling frequency section are substituted into the system discrete time domain frequency analysis model to verify the digital system vulnerability design. As a proper PLC sampling unit is selected, the effective cost control is realized, the system oscillation caused by frequent or lag sampling is prevented, and the system operation stability and reliability are guaranteed.

The invention belongs to the technical field of the operation and control of power systems and particularly relates to a carrier phase shift based control system modeling method for a modular multilevel converter (MMC). According to the carrier phase shift based control system modeling method, an MMC control system based on a CPS-SPWM (Carrier Phase Shifted-Sinusoidal Pulse Widen Modulation) method is divided into four encapsulated control modules, the original control element in each control module is converted into an equivalent control subfunction by using a discrete time domain algorithm, and a large number of control element duplicating work is avoided through repeatedly calling the equivalent control subfunctions; through designing signal interfaces and parameter filling cards of the encapsulated control modules, a large number of control signal dimension converting work in the original modeling process is avoided; in addition, subfunction files compiled by external Fortran can be encrypted through .obj files; each encapsulated module can be used for effectively meeting the requirements on specific control effect and can also be used for reliably realizing the communication of a large amount of data, so that a large number of data signal dimension converting work in the original modeling method is avoided.

The invention discloses a noise power estimation method for OFDM frequency spectrum sensing. According to the method, a continuous time domain radio-frequency signal is received by utilizing an antenna, downconversion and time domain sampling processing are performed on the continuous time domain radio-frequency signal to obtain a discrete time domain baseband signal then, and, finally, noise power is estimated according to the discrete time domain baseband signal. The method is advantageous in that, on the condition that whether the received signal contains an OFDM signal is not known, the noise power can still be effectively estimated.

The invention discloses a magnetic suspension bearing shaft system falling track response recognition method and device based on Hilbert transform, wherein the method comprises the following steps of obtaining a continuous time domain displacement signal of a shaft system; setting the sampling frequency of the continuous time domain displacement signal, and obtaining a discrete time domain displacement signal; obtaining an instantaneous frequency spectrum signal through Hilbert transform; setting cutting-off time duration and a threshold value; solving the variance and expectation of the instantaneous frequency in the cutting-off time; comparing the variance and expectation of the instantaneous frequency with the threshold value; determining the track response of the shaft system. The method has the advantages that only the displacement signal of the shaft system is used; the obtaining is easy; the instantaneous calculation of frequency change can be realized; the real-time performance is good; simplicity, convenience and high speed are realized.

The invention discloses an impulse noise suppression method for sparse iterative covariance estimation in a power line, which comprises the following steps of: at a sending end, transmitting a discrete time domain signal added with a cyclic prefix to a receiving end through a channel; at a receiving end, firstly, projecting a received signal on an empty subcarrier matrix to obtain a mixed signal only containing impulse noise and Gaussian noise; utilizing sparse iterative covariance estimation to obtain the power of the mixed signal so as to obtain the power of the impulse noise; utilizing thelinear mean square error to obtain an estimated value of the impulse noise; subtracting the estimated value of the impulse noise from the received signal to complete suppression of the impulse noise.The method has the advantages that the adopted sparse iterative covariance estimation has higher resolution, and the power of the mixed signal can be estimated more accurately, so that the estimated impulse noise is more accurate, and the suppression effect of the impulse noise is better.