121results about How to "Accurate noise" patented technology

A method comprises processing M subband communication signals and N target-cancelled signals in each subband with a set of beamformer coefficients to obtain an inverse target-cancelled covariance matrix of order N in each band; using a target absence signal to obtain an initial estimate of the noise power in a beamformer output signal averaged over recent frames with target absence in each subband; multiplying the initial noise estimate with a noise correction factor to obtain a refined estimate of the power of the beamformer output noise signal component in each subband; processing the refined estimate with the magnitude of the beamformer output to obtain a postfilter gain value in each subband; processing the beamformer output signal with the postfilter gain value to obtain a postfilter output signal in each subband; and processing the postfilter output subband signals to obtain an enhanced beamformed output signal.

An apparatus for processing an audio signal to obtain control information for a speech enhancement filter has a feature extractor for extracting at least one feature per frequency band of a plurality of frequency bands of a short-time spectral representation of a plurality of short-time spectral representations, where the at least one feature represents a spectral shape of the short-time spectral representation in the frequency band. The apparatus additionally has a feature combiner for combining the at least one feature for each frequency band using combination parameters to obtain the control information for the speech enhancement filter for a time portion of the audio signal. The feature combiner can use a neural network regression method, which is based on combination parameters determined in a training phase for the neural network.

There is provided a matching method, capable of positioning with higher accuracy at higher speed. The method includes the steps of: constructing a pattern model of a registered image in which a plurality of reference points are set on an extracted contour and a corresponding point search line having a predetermined length and passing through each reference point; acquiring an image and acquiring an initial position corresponding to the registered image to arrange the corresponding point search line of the pattern model; finding a corresponding point on the image corresponding to each reference point with regard to each corresponding point search line at a position along the corresponding point search line on the image; and regarding a relation between each reference point and the corresponding point as an evaluation value and performing fine positioning such that an accumulated value of the evaluation values becomes minimal or maximal.

An improved approach to noise estimation permits, for example, tighter closed-loop power control in a wireless communication network with attendant improvements in transmit power efficiency and network capacity. In an exemplary embodiment, the received signal-to-noise ratio (SNR) of a data signal is estimated based on noise samples obtained from one or more other signals received in association with the data signal. In general, these associated signals are characterized by the receiver's ability to extract like valued samples from them, such that pairs of these like valued signal samples may be subtracted, thereby canceling their deterministic signal components and leaving only difference values representative of the non-deterministic noise components of the signal samples. Obtaining difference values from more than one associated signal increases the sample size of difference values used in noise estimation, thereby improving the statistical basis for noise estimation and, therefore, the accuracy of SNR estimation.

A robot includes: an arm driven by a motor; an angle sensor that detects a pivoting angle of the motor; an inertia sensor that detects an inertial force acting on the arm; a noise detecting unit that detects a noise frequency of the inertia sensor from both an output of the angle sensor and an output of the inertia sensor; a filter-constant determining unit that determines a characteristic of a filter from information of the noise detecting unit; and the filter that removes noise of the inertia sensor on the basis of the filter-constant determining unit.

A method for the detection of noise and speech segments in a digital audio input signal, the input signal being divided into a plurality of frames including a first stage in which a first classification of a frame as noise is performed if the mean energy value for this frame and the previous N frames is not greater than a first energy threshold, N>1, a second stage in which for each frame that has not been classified as noise in the first stage it is decided if the frame is classified as noise or as speech based on combining at least a first criterion of spectral similarity of the frame with acoustic noise and speech models, a second criterion of analysis of the energy of the frame and a third criterion of duration, and of using a state machine for detecting the beginning of a segment as an accumulation of a determined number of consecutive frames with acoustic similarity greater than a first threshold and for detecting the end of the segment; a third stage in which the classification as speech or as noise of the signal frames carried out in the second stage is reviewed using criteria of duration.

An image display method includes displaying a captured image, if an object, which is included in the captured image that is displayed, is selected, detecting a boundary of the selected object, discriminating between the object and a remaining image region other than the object based on the detected boundary of the object, and discriminatingly displaying the object through application of different effects to the object and the remaining image region.

By using a high-range sub-band signal, a correction coefficient corresponding to importance of auditory sense is calculated to correct a noise level and generate additional signal information, thereby accurately reflecting the noise level of the sub-band important in the auditory sense. Thus, it is possible to calculate additional signal information reflecting the noise level of the sub-band important in the auditory sense according to importance with a small calculation amount. The calculation amount can further be reduced by using a correction coefficient based on the characteristic of an ordinary audio signal.

The filter coefficients of an adaptive notch filter are sequentially updated to minimize an error signal based on the error signal and a first reference signal which is produced by subtracting a signal which represents the product of a sine corrective value C1 and a reference sine signal, from a signal which represents the product of a cosine corrective value C0 and a reference cosine signal. The filter coefficients of an adaptive notch filter are sequentially updated to minimize the error signal based on the error signal and a second reference signal which is produced by adding a signal which represents the product of the reference sine signal and the cosine corrective value C0 and a signal which represents the product of the reference cosine signal and the sine corrective value C1 to each other.

Intensity data of the signals produced by an ion detector are sequentially stored in a data processor, with each piece of intensity data being associated with time t required for each of the various ions ejected from an ion trap to fly through a time-of-flight space and reach the ion detector. The data obtained within a time range T2 corresponding to a measurement mass range are extracted as profile data. The data obtained within either a time range T1 before the arrival of an ion having the smallest m/z value or a time range T3 after the arrival of an ion having the largest m/z value are extracted as noise component data. Various kinds of noise information such as the noise level or standard deviation are calculated from the noise component data. Based on this noise information, a noise component is removed from the profile data. For every mass scan cycle, the noise component data and profile data are almost simultaneously obtained. Therefore, even if the electrical noise from the ion detector changes with time, the noise can be properly removed with little influence from that change of the noise.

The invention discloses a vein needle conduit assembling machine, comprising a rack and a conveying device for conveying the vein needle conduit assemblies. A straw assembly mechanism, a needle seat feeding mechanism, an internal glue adding assembly, a needle handle feeding mechanism, a drying mechanism, a conicity detection device, a conduit ventilation detection device, a pulling force detection device and a conduit unloading device are successively arranged on the rack from the left to the right and are connected through the conveying device; and the straw assembly mechanism is connected to a conduit storage mechanism. The vein needle conduit assembling machine can finish whole vein needle conduit assembly and does not need artificial contact on the vein needle assemblies, so that the vein needle is not easy to get pathogen during a packaging process and safety can be guaranteed. Besides, the vein needle conduit assembling machine is high in automation degree, high in assembling efficiency, beneficial for mass production, reasonable in design, simple in structure and strong in practicability.

Noise factor of a radio-frequency device under test (DUT) is determined by driving the input of the DUT with a randomly modulated sine wave and measuring the power of a resulting DUT OUTPUT signal within each of a set of equally-sized frequency bands. The noise factor is computed as a combination of the power of the modulated sine wave within each of a plurality of frequency bands and the measured power of the DUT OUTPUT signal within that same plurality of frequency bands.

A system and method of characterizing a device under test wherein a signal is injected into the device under test, the response to the injected signal is measured to determine the impedance of the device under test in the frequency domain, the impedance is converted to the time domain, and the voltage noise of the device under test is calculated based on the impedance of the device under test in the time domain.

For voltage values (observed noise sequence) in an electronic power line (communication medium) which are obtained at a predetermined interval, initial values of noise characteristics based on a statistic of the observed noise sequence itself are decided by a moment method (S301 to S307), the noise characteristics (state transition probabilities and state noise power) for maximization of the likelihood of the observed noise sequence are obtained from the initial values by MAP (Maximum A Posteriori) estimation using a Baum-Welch algorithm (S309 to S312), a state sequence is estimated from the obtained noise characteristics, and an impulsive noise at each time point is detected.

An electronic cryptographic device (100) comprising a physically unclonable function (PUF) (110) and an enrollment unit (142) arranged to generate a first PUF data during the enrollment phase, the first PUF data being derived from a first noisy bit string of the PUF, the first PUF data uniquely identifying the physically unclonable function, the first PUF data comprising a first helper data. The first PUF data is transmitted to an electronic server during an enrollment phase. The device comprises a use-phase unit (144) arranged to generate a second PUF data derived from a second noisy bit string during a use phase. The first helper data is received from the server in response to transmitting the second PUF data. An error corrector (160) is arranged to apply the first helper data to the second noisy bit string.

In a display device with optical sensors, a recognition processing portion (22) performs recognition processing on a scan picture generated by optical sensors (2), and calculates a position. A mode control portion (24) determines whether or not the mode is standby so that the recognition processing portion (22) is stopped from operating. At the time of transition to the standby mode, decimated image memory (25) stores a decimated image with a decreased number of pixels. The mode control portion (24) performs pixel-by-pixel comparison between the stored decimated image and a decimated image supplied anew, and exits the standby mode when the number of pixels whose difference in pixel values is greater than or equal to a first threshold is greater than or equal to a second threshold. Here, the first and second thresholds are appropriately set in accordance with an ambient luminance L from a luminance sensor (20), and therefore, any change in the image can be accurately distinguished from noise, thereby preventing the standby mode from being or not being cancelled by mistake.

The invention discloses an unsupervised noise estimation and speech enhancement method based on a separable deep automatic encoding technology. The method comprises a step of prior processing and a step of speech enhancement on unknown noise pollution. The method can be flexibly applied to various speech processing scenes. The method is not constrained by a language of a speech content, changes of a speaker, and a kind of noise. Compared with classical stationarity assumption-based spectral estimation algorithm SS (Spectrum Subtraction) and MMSE (Minimum Mean Square Error), the method does not rely on stationarity assumption and can accurately estimate spectrums for stationary or abrupt noise. Compared with algorithm based on a hidden Markov model and a linear prediction coefficient, the method does not need to specify the type of the processed non-stationary noise. Compared with a noise estimation method based on a low rank structure, noise in the method does not need to have a low-rank repeated structure.

A method of noise analysis and correction of noise violations for an integrated circuit design includes steps of (a) receiving as input a standard parasitic exchange file for an integrated circuit design; (b) parsing the standard parasitic exchange file to generate a resistance graph; (c) generating a representation of the resistance graph to determine noise critical nets; (d) generating a list of only noise critical nets from the representation of the resistance graph; (e) selecting a net from the list of only noise critical nets; (f) calculating a value of total crosstalk noise in the selected net from all aggressor nets relative to the selected net; and (g) generating as output the value of total crosstalk noise in the selected net for correcting a noise violation.

The sound source tracking device of the present invention comprises a plurality of differential microphones having bidirectionality, and a support member adapted to support the plurality of differential microphones such that the plurality of differential microphones are disposed in an array within a given plane. The plurality of differential microphones are supported on the support member such that their principal axes of directionality are approximately orthogonal to the given plane.