30 results about "Fast ica" patented technology

The invention discloses a soft separation method of conducted electromagnetic interference noise based on a blind signal processing technology, belonging to the field of conducted electromagnetic interference noise inhibition. The method comprises the following steps of: carrying out probe frequency spectrum estimation and compensation on two current probes; simultaneously measuring electromagnetic interference noise time domain signals on a live wire and a middle wire of an electronic system by the two current probes and a double-trace oscilloscope; carrying out blind separation on electromagnetic interference noise by utilizing a Fast ICA (Independent Component Analysis) algorithm in a blind signal processing method to obtain a signal source vector estimation value; and finally, judging the property of separation signals based on the maximum cross correlation coefficient of blind separation signals and common mode or differential mode reference signals. The invention overcomes the defects of using a radiofrequency transformer or a power divider to carry out hard separation on common mode noise and differential mode noise, has the advantages of high separation accuracy and favorable practicability, and lowers the cost.

A system and method for detecting a functional signal in retinal images. An optical imaging device comprises a stimulation light source, an interrogating light source, and a detector. The retina is stimulated by the stimulation light source. The retina is then illuminated by an interrogation light, and the reflected intensity from the retina is measured at an interrogating spectral band that indicates the state of hemoglobin saturation before and after visual stimulation. The optical changes that result from retinal neuronal activity are captured by the detector. The signal representing the state of hemoglobin saturation before and after visual stimulation is isolated. In an embodiment of the present invention, this signal is isolated using principle components analysis (PCA). In another embodiment of the present invention, blind source separation (BSS) and independent component analysis (ICA) algorithms such as extended spatial decorrelation and fast-ICA are used to isolate the functional signal from the retinal videos.

The invention discloses a no-reference fuzzy distorted stereo image quality evaluation method, which comprises the following steps: in a training stage, selecting a plurality of undistorted stereo images and corresponding fuzzy distorted stereo images to form a training image set; then, carrying out a dictionary training operation by a Fast-ICA (independent component analysis) method, and constructing a visual dictionary table of each image in the training image set; constructing the visual quality table of the visual dictionary table of each distorted stereo image by calculating a distance between the visual dictionary table of each undistorted stereo image and the visual dictionary table of each corresponding fuzzy distorted stereo image; in a testing stage, for any one tested stereo image, carrying out non-overlapping partitioning processing to a left sight point image and a right sight point image of the tested stereo image; and according to the constructed visual dictionary table and the constructed visual quality table, obtaining an objective evaluation prediction value of the image quality of the tested stereo image. The no-reference fuzzy distorted stereo image quality evaluation method has the advantages of low computation complexity and good relevance between an objective evaluation result and subjective perception.

The invention discloses a method for objectively evaluating the quality of a three-dimensional image without a reference. According to the method for objectively evaluating the quality of the three-dimensional image without the reference, in the training stage, multiple original undistorted three-dimensional images and corresponding distorted three-dimensional images are selected to form a training image set, then dictionary training is conducted according to the Fast-ICA method, so that the visual dictionary table of each image in the training image set is constructed, and visual quality tables corresponding to the visual dictionary tables are constructed by calculating the frequency responses of each pixel point in each original undistorted three-dimensional image and each pixel point in the corresponding distorted three-dimensional image in the training image set under the conditions of different center frequencies and different directional factors; in the testing stage, for the tested three-dimensional image, a predicted objective evaluation value of the quality of the tested three-dimensional image is obtained by calculating the frequency responses of each pixel point in the tested three-dimensional image under the conditions of different center frequencies and different directional factors according to the constructed visual dictionary tables and the constructed visual quality tables. The method for objectively evaluating the quality of the three-dimensional image without the reference has the advantages that calculation complexity is low, and the relevancy between objective evaluation results and subjective sensing is high.

The invention discloses a high-precision denoising method for a local ultrasonic array signal, which comprises the following steps of: separating a multi-channel array signal into statistical independent components by using a fast independent component Fast ICA, carrying out autocorrelation analysis on the independent components, and preliminarily eliminating the influence of noise; Further denoising the signal of each channel by using an ensemble empirical mode decomposition (EEMD) algorithm; And recombining the signals subjected to fine denoising to obtain high-precision denoised signals. According to the method, the defects that traditional EMD decomposition can only denoise a single sensor and a single channel signal, and FastICA can only roughly denoise an array signal are overcome, too large direction finding and positioning errors caused by interference of on-site noise signals are avoided, and therefore the ultrasonic array signal denoising effect and the direction finding andpositioning precision are improved.

The invention discloses a multi-feature fusion cognitive underwater acoustic communication space-fast time adaptive processing algorithm. The algorithm includes the following steps: introducing an interference feature analysis-based interference cognitive function on the basis of a traditional space-fast time adaptive array processing algorithm; calculating the number of interference sources by using an array covariance matrix feature decomposition mode, and estimating the direction of a target user and the direction of interference incoming waves by adopting a MUSIC spatial spectrum analysismode; separating interference signals by using a negentropy maximized Fast-ICA based blind source separation algorithm, analyzing time domain features by using an envelope detection mode, analyzing the time-frequency spectrum by using a short-time Fourier transform mode, and further extracting interference features to identify interference types; and finally, selecting appropriate interference samples to perform space-fast time adaptive cancellation according to the interference types, and further improving the convergence speed of the adaptive algorithm. The beneficial effects are that: the dimensionality reduction processing and cancellation sample selection of the space-fast time adaptive algorithm can be realized, and the fast and reliable convergence of the space-fast time adaptive processing can be guaranteed.

The invention discloses a multi-user period long-short code DS signal pseudo code blindness estimation method; the method can model multi-user period long-short code DS signals with complex structures into a blind separation mode according to short spreading code and long scrambling code periods; the method comprises the following steps: using a Fast-ICA algorithm to separate mixed PN sequence segments of all users, and regrouping a fuzzy sequence; using the m sequence shift superposition property, and using a secondary delay phase multiplication to eliminate information code and spreading code influences; combining a cyclotomic coset theory to calculate signal third order correlation functions, thus determining the user mixed PN sequence and third order correlation peak point, using a matrix inclined resolving method to finish scrambling code estimation, and using a segment delay cross correlation method to finish the spreading code estimation after the signals are descrambled. The method can fully utilize the Fast-ICA algorithm and m sequence third order correlation characteristics, thus realizing blind estimation of two pseudo hatted codesof the multi-user period long-short code DS signals.

The invention discloses a magnetic induction cardiopulmonary activity signal separation method based on a Fast-ICA method. The magnetic induction cardiopulmonary activity signal separation method includes the following steps: sending magnetic induction signals of the left chest and the right chest into a 12MHz narrow-band filter to filter the signals to obtain a left chest phase difference signal and a right chest phase difference signal, conducting wavelet denoising on the left chest phase difference signal and the right chest phase difference signal, adopting the independent variable analyzing method (Fast-ICA) to separate a heartbeat signal and a respiratory signal to achieve synchronous monitoring of magnetic induction cardiopulmonary activity.

The invention discloses a multi-antenna OFDMA signal decoding method based on rapid and independent component analysis. The method comprises the following steps: step 1, establishing a signal model for meeting the requirement of a rapid and independent component analysis algorithm on an input signal; step 2, conducting PCA whitening on an observation vector under Gaussian noise; step 3, separating a plurality of user information modulated on OFDMA subcarriers without knowing any information about the subcarriers; and step 4, performing subcarrier sequence estimation and OFDMA user identification. According to the method, mathematical statistical modeling is conducted on multi-antenna OFDMA signals based on Fast-ICA, and blind channel estimation and decoding are also performed, so that the signal energy is increased without removing a cyclic prefix, and the decoding performance is improved. Through adoption of the method, timing is not needed at a receiving end, blind separation and decoding are conducted on the OFDMA signals, and the decoding performance is good.

The invention discloses a long-short code estimation method of a multi-speed long-short code direct sequence-code division multiple access signal. Firstly, according to the largest long scrambling code cycle and the smallest spreading code cycle of a received signal, the received signal is segmented twice to obtain a signal matrix, and according to a Fast-ICA algorithm, complex code fragments of all users are obtained through separation; then, with gradual reducing of information speeds, a user long-short code sequence is estimated, the complex code fragments obtained by separating the Fast-ICA algorithm are spliced to constitute a fuzzy sequence, a secondary delay multiplying method is adopted to remove sequence fuzziness and spreading code interference, and in combination of a cyclotomiccoset and three-order relevant characteristics and according to a characteristic information matching method, long interference code estimation corresponding to all users at the same speed is completed; meanwhile, relevant calculation estimates the short spreading code, and then through a similarity coefficient matrix, all the complex code fragments of the estimated users are removed till long-short code estimation of all the users is completed.

The present invention relates to a FAST-ICA algorithm-based ultrathin plate interference signal separating and processing method during the wavelength phase-shifting process. According to the technical scheme of the invention, an ultrathin plate interference signal is obtained through the wavelength phase-shifting interference measurement, and then the FAST-ICA algorithm is introduced based on the blind signal separation technology. Through the fast iterative algorithm, interference fringes formed between the front and back surfaces of an ultrathin plate are separated. After that, separated interference fringes are processed through the time-domain phase-shifting algorithm. In this way, the surface shape information of the front and back surfaces of the ultrathin plate is obtained. The method mainly aims to process the stripe graph of the ultrathin plate during the wavelength phase-shifting process. Therefore, the method can be used for separating the information of the front and back surfaces of the ultrathin plate and realizes the separation and the measurement of the surface shapes of the front and back surfaces of the ultrathin plate.

The invention discloses a no-reference image quality evaluation method based on independent component analysis. The method comprises the following steps: selecting an image quality block representingimage quality by utilizing spatial correlation of pixel pairs; Using the selected optimal image quality block and adopting a Fast ICA algorithm to obtain detection characteristics of images in an LIVE2 image library, and obtaining independent components of the image quality block according to the characteristics; Establishing a hash lookup table by taking binaryzation of independent components ofan image in LIVE2 as a hash function, wherein each data element of the lookup table comprises judgment data, independent component data and a subjective quality evaluation (DMOS) value; And searchingthe hash table by using binaryzation of independent components of the image to be detected, and performing Hamming distance matching on the conflict item to obtain a no-reference image quality evaluation result. The evaluation result and the DMOS value keep good consistency, and the distortion degree of the image can be measured accurately.

The invention provides a fetal electrocardiogram monitoring system based on an Android smartphone so as to achieve home monitoring of the fetal electrocardiogram. The system is composed of a pregnantwoman abdomen three-lead electrocardiogram collector, a fetal electrocardiogram real-time algorithm and Android smartphone software. The circuit of the pregnant woman abdomen three-lead electrocardiogram collector is mainly composed of a low-power-consumption Bluetooth processor Cypress CY8C4247 and a three-lead analog front end ADS1293, and pregnant woman abdomen three-lead electrocardiogram signals are collected by the 24-bit ADS1293, transmitted to the processor CY8C4247 through SPI communication to be processed and then wirelessly sent to the Android smartphone through Bluetooth. The functions of the Android smartphone software include BLE service acquisition, communication connection, Service provision, broadcasting, thread establishment and drawing canvas design, heart rate calculation, electrocardiogram abnormity warning and the like. The fetal electrocardiogram detection algorithm is a fast ICA algorithm with optimized parameters.

The invention discloses a detection and accurate positioning method for a small leak source of a pressure pipe. Acoustic emission leak detection technology is adopted, based on a mutual correlation positioning theory and the characteristics that a quantitative calculation result is high in objectivity and reliability of the theory, a positioning model for detecting a small leak source of a pressure pipe is established. Based on the basis that a collection signal is treated through combination of modal acoustic emission technology and wavelet transform, isolated component analysis technology is introduced, isolation analysis of a positioning signal of the small leak source is achieved through a Fast ICA tool box for fast analysis of isolated components, and a multi-point positioning calculated result with high precision is obtained. According to the method, the effect between small leak source signals is reduced, positioning data for multi-point mall leak source is separated, and positioning for a small leak source of a pressure pipe is accurate.

The invention discloses an unbalanced source positioning method, system and device. The method comprises the following steps of establishing a negative-sequence Norton equivalent circuit diagram for unbalanced source positioning at a common connection point; acquiring three-phase imbalanced data generated by an upstream side unbalanced load and a downstream side unbalanced load at the common connection point; separating the upstream side impedance and the downstream side impedance in the three-phase imbalanced data through a negative entropy-based Fast ICA algorithm; calculating, according tothe upstream side impedance and the downstream side impedance, an upstream side unbalanced voltage of the upstream side unbalanced load at the common connection point and a downstream side unbalancedvoltage of the downstream side load at the common connection point; and determining the position of a dominant unbalanced source by using the upstream side unbalanced voltage and the downstream side unbalanced voltage. The unbalanced source positioning method provided by the invention can quickly position the dominant unbalanced source, so that staff can take appropriate measures in time for the dominant unbalanced source.