1655 results about "Noise component" patented technology

Embodiments of the present invention relate to methods, systems, and computer program products for signal processing. A first plurality of microphone signals is obtained by a first microphone array. A second plurality of microphone signals is obtained by a second microphone array different from the first microphone array. The first plurality of microphone signals is beamformed by a first beamformer comprising beamforming weights to obtain a first beamformed signal. The second plurality of microphone signals is beamformed by a second beamformer comprising the same beamforming weights as the first beamformer to obtain a second beamformed signal. The beamforming weights are adjusted such that the power density of echo components and/or noise components present in the first and second plurality of microphone signals is substantially reduced.

A method and apparatus extract a signal component of a measured signal using one of two methods. If the signal component in the measured signal is a periodic signal with a certain well-defined peak-to-peak intensity value, upper and lower envelopes of the measured signal are determined and analyzed to extract said signal component of the measured signal. This signal component can further be used to calculate a desired parameter of the sample. The DC component of the signal is determined as the median value of the upper envelope, and the AC component is determined as the median value of the difference between the upper and lower envelopes. If the signal component of the measured signal is a periodic signal characterized by a specific asymmetric shape, a specific adaptive filtering is applied to the measured signal, resulting in the enhancement of the signal component relative to a noise component. This adaptive filtering is based on a derivative of the Gaussian Kernel having specific parameters matching the characteristics of the signal component.

Systems and methods for noise suppression using noise subtraction processing are provided. The noise subtraction processing comprises receiving at least a primary and a secondary acoustic signal. A desired signal component may be calculated and subtracted from the secondary acoustic signal to obtaining a noise component signal. A determination may be made of a reference energy ratio and a prediction energy ratio. A determination may be made as to whether to adjust the noise component signal based partially on the reference energy ratio and partially on the prediction energy ratio. The noise component signal may be adjusted or frozen based on the determination. The noise component signal may then be removed from the primary acoustic signal to generate a noise subtracted signal which may be outputted.

One embodiment of the present invention relates to an adaptive filtering apparatus comprising first and second real valued adaptive filters, respectively configured to receive an adaptive filter input signal based upon a transmission signal in a transmission path. The first real valued adaptive filter is configured to operate a real valued adaptive filter algorithm on the input signal to estimate a first intermodulation noise component (e.g., an in-phase component) in a desired signal and to cancel the estimated noise. The second real valued adaptive filter is configured to operate a real valued adaptive filter algorithm on the input signal to estimate a second intermodulation noise component (e.g., a quadrature phase component) in the desired signal and to cancel the estimated noise. Accordingly, each filter operates a real valued adaptive algorithm to cancel a noise component, thereby removing complex cross terms between the components from the adaptive filtering process.

A radio receiver supporting cancellation of thermal and phase noise in a down-converted RF signal. An inbound RF signal and blocking signal are provided directly to a passive mixer for down-conversion into a first baseband signal having data, thermal noise, and reciprocal mixing (RM) noise components. The inbound signals are also provided to a transconductance circuit, the output of which is provided to a second passive mixer for conversion into a current signal having data and blocking signal components, and a RM image. The blocking signal component and the RM image are mixed with a second LO signal, derived from the blocking signal, to produce a RM noise cancellation signal. The data component of the current signal is converted into a second baseband signal having data and thermal noise components. The first baseband signal, second baseband signal and RM noise cancellation signal are then combined through harmonic recombination.

A noise suppressing device receives sound signals through a plurality of sound-receiving units and suppresses noise components included in the input sound signals. The noise suppressing device includes a detecting unit which detects a usage pattern of the noise suppressing device from a plurality of usage patterns in which positional relationships of the plurality of sound-receiving units and/or positional relationships between the plurality of sound-receiving units and a target sound source are different from each other, a converting unit which converts using environment information used in anoise suppressing process to each of the sound signals inputted by the plurality of sound-receiving units into using environment information in accordance with a usage pattern detected by the detecting unit and a suppressing unit which performs the noise suppressing process using the using environment information converted by the converting unit to the sound signals.

A noise suppressing device is provided for suppressing noise of a first audio signal to generate a second audio signal. In the noise suppressing device, a noise acquisition unit acquires a plurality of noise components which are different from each other. A noise suppression unit generates each suppression component by suppressing each noise component from the first audio signal, thereby providing a plurality of suppression components different from each other in correspondence to the plurality of the noise components. A signal generation unit generates the second audio signal by summing the plurality of the suppression components that are provided from the noise suppression unit.

In order to accurately remove an unnecessary periodic noise component from an image, a reconstruction unit generates a reconstructed image without a periodic noise component by fitting to a face region detected in an image by a face detection unit a mathematical model generated according a method of AAM using a plurality of sample images representing human faces without a periodic noise component. The periodic noise component is extracted by a difference between the face region and the reconstructed image, and a frequency of the noise component is determined. The noise component of the determined frequency is then removed from the image.

An active dry sensor module for measurement of bioelectricity is disclosed. The active dry sensor module of the present invention excludes the use of a conductive gel, thereby not supplying unpleasantness and discomfort to a reagent and preventing the interference of the signal due to a noise component. Further, the active dry sensor module of the present invention amplifies the biomedical signal to a desired level, thereby precisely and easily measuring the biomedical signal.

A capacitive touch panel capable of reducing a disturbance noise and reducing touch detection time with a simple structure is obtained. The capacitive touch panel includes: a plurality of drive electrodes each to which a drive signal for touch detection is applied; a plurality of touch detection electrodes arranged to intersect the plurality of drive electrodes, and each outputting a detection signal synchronized with the drive signal; a first sampling circuit (A/D conversion circuits 72 and 73) extracting a first series of sampling signal including a signal component with first level and a noise component, from the detection signal; a second sampling circuit (A/D conversion circuits 75 and 76) extracting a second series of sampling signal including a signal component with second level different from the first level and the noise component, from the detection signal; a filter circuit (digital LPFs 81 and 82) performing a high range cut process on the first series of sampling signal and the second series of sampling signal; and a computation circuit (a subtraction circuit 90) determining a signal for touch detection based on an output of the filter circuit.

An image processing device includes: a frequency divider for performing a frequency division processing of dividing an input image into a plurality of frequency components each having a frequency band; a noise remover for performing a noise component removal processing of removing a noise component from a high frequency component in the frequency components each having the frequency band obtained by the frequency division processing by the frequency divider; an edge preservation information calculator for detecting an edge intensity based on a low frequency component in the frequency components each having the frequency band obtained by the frequency division processing by the frequency divider, and calculating edge preservation information relating to a degree of preserving an edge component based on the detected edge intensity; an edge preserving section for preserving the edge component in the high frequency component, based on the edge preservation information calculated by the edge preservation information calculator; and a frequency synthesizer for synthesizing the high frequency component whose noise component is removed by the noise remover and whose edge component is preserved by the edge preserving section, and the low frequency component, in each of the frequency bands.

The present technology provides adaptive noise reduction of an acoustic signal using a sophisticated level of control to balance the tradeoff between speech loss distortion and noise reduction. The energy level of a noise component in a sub-band signal of the acoustic signal is reduced based on an estimated signal-to-noise ratio of the sub-band signal, and further on an estimated threshold level of speech distortion in the sub-band signal. In embodiments, the energy level of the noise component in the sub-band signal may be reduced to no less than a residual noise target level. Such a target level may be defined as a level at which the noise component ceases to be perceptible.

The present invention is directed to a wireless telephone having a first microphone and a second microphone and a method for processing audio signal in a wireless telephone having a first microphone and a second microphone. The wireless telephone includes a first microphone, a second microphone, and a signal processor. The first microphone outputs a first audio signal, the first audio signal comprising a voice component and a background noise component. The second microphone outputs a second audio signal. The signal processor increases a ratio of the voice component to the noise component of the first audio signal based on the content of at least one of the first audio signal and the second audio signal to produce a third audio signal.

An image processing system uses centralized image correction data to process digital images. The image processing system includes a centralized database for storing image correction data for imaging devices. An image processor that receives image data representing an image captured by one of the imaging devices accesses the centralized database with a key associated with the imaging device to retrieve the image correction data for the imaging device. The image processor processes the image data using the retrieved image correction data to correct the image data by reducing various noise components in the image.

A noise reduction device is configured by use of: means for calculating a predetermined constant, and a predetermined reference signal Rω(T) in the frequency domain, respectively by use of adaptive coefficients Wω(m), and for thereby obtaining estimated values Nω and Qω(T) respectively of stationary noise components, and non-stationary noise components corresponding to the reference signal, which are included in a predetermined observed signal Xω(T) in the frequency domain; means and for applying a noise reduction process to the observed signal on the basis of each of the estimated values, and for updating each of the adaptive coefficients on the basis of a result of the process; and an adaptive learning means and for repeating the obtaining of the estimated values and the updating of the adaptive coefficients, and for thereby learning each of the adaptive coefficients.

A microphone system has a base coupled with first and second microphone apparatuses. The first microphone apparatus is capable of producing a first output signal having a noise component, while the second microphone apparatus is capable of producing a second output signal. The system also has combining logic operatively coupled with the first microphone apparatus and the second microphone apparatus. The combining logic uses the second output signal to remove at least a portion of the noise component from the first output signal.

The present invention is directed to improved speech intelligibility in telephones with multiple microphones. Such a telephone includes a first microphone, a second microphone, a voice activity detector (VAD), a receiver module, and a signal processor. The first microphone outputs a first audio signal, which comprises a voice component when a near-end user talks and a background noise component. The second microphone outputs a second audio signal. The VAD generates a voice activity signal responsive to a ratio between the first audio signal and the second audio signal. The voice activity signal identifies time intervals in which the voice component of the near-end user is present in the first audio signal. The receiver module receives a third audio signal, which comprises a voice component of a far-end user. The signal processor modifies the third audio signal responsive to the voice activity signal.

A circuit and method for reducing noise in video imagers which takes advantage of the fact that the same image information is present in the drain current in a reset transistor used to reset a photodiode in a pixel as is present in the readout current. The noise is reduced by passing the multiplexed output voltage from the source follower output transistor in an APS imager system through a high pass filter to reduce the low frequency noise from the source follower. The drain current in the reset transistor used to reset the APS is passed through a low pass filter. The low pass filter output and the high pass filter output are then combined. Since the drain current in the reset transistor contains the same image information as the voltage output of the source follower output transistor the image information can be obtained by combining the output of the low pass filter and the output of the high pass filter. Since the low frequency noise components of the source follower output transistor have been suppressed combined outputs of the low pass filter and high pass filter will provide the image information with greatly suppressed low frequency noise.

A speech enhancement system improves the perceptual quality of a processed voice signal. The system improves the perceptual quality of a voice signal by removing unwanted noise components from a voice signal. The system removes undesirable signals that may result in the loss of information. The system receives and analyzes signals to determine whether an undesired random or persistent signal corresponds to one or more modeled noises. When one or more noise components are detected, the noise components are substantially removed or dampened from the signal to provide a less noisy voice signal.

Kernels (206) for use in learning machines, such as support vector machines, and methods are provided for selection and construction of such kernels are controlled by the nature of the data to be analyzed (203). In particular, data which may possess characteristics such as structure, for example DNA sequences, documents; graphs, signals, such as ECG signals and microarray expression profiles; spectra; images; spatio-temporal data; and relational data, and which may possess invariances or noise components that can interfere with the ability to accurately extract the desired information. Where structured datasets are analyzed, locational kernels are defined to provide measures of similarity among data points (210). The locational kernels are then combined to generate the decision function, or kernel. Where invariance transformations or noise is present, tangent vectors are defined to identify relationships between the invariance or noise and the data points (222). A covariance matrix is formed using the tangent vectors, then used in generation of the kernel.

PCT No. PCT/JP98/01128 Sec. 371 Date Nov. 4, 1998 Sec. 102(e) Date Nov. 4, 1998 PCT Filed Mar. 17, 1998 PCT Pub. No. WO98/41143 PCT Pub. Date Sep. 24, 1998The present invention relates to a pulse wave detecting device for detecting pulse waves, and to a pulse measurer employing this pulse wave detecting device. The present invention addresses the problem of obtaining a pulse wave signal in which the noise components have been suitably removed from a pulse waveform, and of determining the pulse rate with high accuracy based on this pulse wave signal. The method for deriving the pulse wave signal and pulse rate is as follows. The pulse wave signal from pulse wave detecting sensor unit (30) is temporarily stored in buffer (503). When impulse noise is detected in the pulse wave signal in buffer (503) by impulse noise detecting means (505), the band pass for first digital filter (506) becomes a hill-shaped curve centered on the frequency corresponding to the preceding pulse rate, and impulse noise in the pulse wave signal output from buffer (503) is decreased. Thereafter, overall noise and body movement components are decreased in the pulse wave signal by means of second digital filter (507) and third digital filter (508). The signal is then subjected to frequency analysis by frequency analyzer (509), and the pulse rate is calculated from the results of this analysis.