1901 results about "Mean square" patented technology

A wireless communications adapts its mode of operation between spatial multiplexing and non-spatial multiplexing in response to transmission-specific variables. An embodiment of a wireless communications system for transmitting information between a base transceiver station and a subscriber unit includes mode determination logic. The mode determination logic is in communication with the base transceiver station and the subscriber unit. The mode determination logic determines, in response to a received signal, if a subscriber datastream should be transmitted between the base transceiver station and the subscriber unit utilizing spatial multiplexing or non-spatial multiplexing. In an embodiment, the mode determination logic has an input for receiving a measure of a transmission characteristic related to the received signal. In an embodiment, the mode determination logic includes logic for comparing the measured transmission characteristic to a transmission characteristic threshold and for selecting one of spatial multiplexing and non-spatial multiplexing in response to the comparison of the measured transmission characteristic to the transmission characteristic threshold. In an embodiment, the transmission characteristic includes at least one of delay spread, post-processing signal-to-noise ratio, cyclical redundancy check (CRC) failure, residual inter-symbol interference, mean square error, coherence time, and path loss. By adapting the mode of operation in response to transmission-specific variables, the use of spatial multiplexing can be discontinued in unfavorable conditions. Additionally, because the wireless communications system can adapt its mode of operation between spatial multiplexing and non-spatial multiplexing, the communications system is compatible with both subscriber units that support spatial multiplexing and subscriber units that do not support spatial multiplexing.

An equalization system and method. In a most general sense, the inventive equalization system includes first and second filters for filtering an in-phase component of a received signal in accordance with first and second sets of coefficients, respectively. The system includes third and fourth filters for filtering a quadrature component of the input signal in accordance with third and fourth sets of coefficients, respectively. The outputs of the first and third filters are subtracted to provide an equalized in-phase output signal and the outputs of the second and fourth filters are added to provide an equalized quadrature output signal. In the illustrative embodiment the filters are finite impulse response filters and the coefficients are provided by a microprocessor. In accordance with the present teachings, the filters are implemented in a general purpose filter. The delay elements of the filters are calculated in accordance with a mean square error algorithm. Accordingly, the coefficients are the product of the correlation between inputs to the delay elements and a cross correlation between the inputs and a set of values representative of a desired response.

Disclosed is a method of estimating repeatable runout (RRO) for a disk drive. The method includes: determining a plurality of position error signal (PES) values for a plurality of servo wedges of a track of a disk; and estimating repeatable runout (RRO) in the PES values for the servo wedges of the track by averaging determined PES values over a pre-determined number of revolutions of the disk of the disk drive and scaling the averaged PES values by a pre-determined ratio of the variance of non-repeatable runout (NRRO) to the variance of an optimal estimation of the RRO for the disk drive.

Camera-assisted tracking of point objects in a radar system is provided. An extended Kalman filter framework based on both radar and camera observations is used to track point objects detected in frames of radar signal data. This framework provides a minimum mean square estimation of the current state of a point object based on previous and current observations from both frames of radar signals and corresponding camera images.

An impluse response h_mn(q) of each transmission path is estimated from N received signals r_m (m=1, . . . , M) and a known signal (for a number of users equal to N, n=1, . . . , N). M×N matrix H (q) having h_mn(q) as an element and a Q×Q matrix H having H(q) as an element are determined (where Q represents a number of multipaths of each transmitted wave and q=0, . . . , Q−1). A soft decision value b′_n(k) is determined from decoded λ₂ [b_n(k)], and this is used to generate an interference component matrix B′(k) to generate an interference replica H·B′(k). The interference replica H·B′(k) is subtracted from a received matrix y(k) to determine y′(k). y(k) and H are used to determine an adaptive filter coefficient w_n(k) to be applied to an n-th user in order to eliminate residual interference components in y′(k) according to the minimum mean square error criteria. y(k) is passed through w_n(k) to provide a log-likelihood ratio as a received signal from the user n from which interferences are eliminated.

The invention provides an attitude estimation method of a maneuvering acceleration-assisted extended Kalman filter (EKF) attitude and heading reference system (AHRS). The state quantity of the EKF contains an error of three attitude angles, a null bias error of a three-axis gyroscope and a three-axis carrier maneuvering acceleration error of a carrier system, and the observed quantity of the EKF contains a three-axis acceleration error and a three-axis earth magnetic field error. A strapdown attitude algorithm and the nine-state EKF algorithm are subjected to data fusion to acquire attitude estimation of the AHRS. A single-axis turntable experiment, a vehicle-mounted dynamic experiment and a flight experiment prove that the maneuvering acceleration-assisted nine-state EKF data fusion algorithm has stable attitude angle accuracy under different maneuvering conditions, and the mean square deviation of the attitude angle can be limited within 2 degrees.

A dynamic channel allocation method and system for use in a wireless network operates by monitoring at least the allocated channel allocated to a particular network node to generate one or more channel metrics relating to radio conditions on the channel. The metrics generated are Received signal power, signal to noise ratio of transmissions on the network and long-term mean square of the equaliser error used in each terminal. The generated metrics are communicated back to the cell access point or the network control server over a signalling channel, and a new frequency is allocated to the cell if it is determined from the metrics that the presently allocated channel is suffering interference. The signalling channel is preferably an ATM VPI/VCI pair, such that signalling messages are transmitted as ATM cells which can be communicated across the wireless channel using the sane signalling frame as is used for payload cells.

The invention discloses a video compression method based on the deep neural network. The method includes the following steps that a video image data set is collected and organized, and a neural network training set, a test set and a cross validation set are constructed; the multi-layer deep neural network is set up; for inter-frame prediction, a motion estimation algorithm is used for searching for the optimal matching block, and residuals and the mean square error of inter-frame prediction are calculated; the residuals obtained after prediction are used as new training data to train a residual code network, and a residual network model comprises an intra-frame residual and an inter-frame residual; compression data serving as fixed-length code streams together with output data, obtained after quantization and lossless entropy coding, of the residual neural network is predicted; a decoding terminal restores the compression data through a neutral network symmetric with a coding terminal, and a compressed image is obtained through reestablishment and recovery. Compared with a traditional H.264 video coding method in equality comparison of plenty of test video sequences, the video compression method can save about 26% code rate on the premise of equal quality.

The invention discloses a drive control method for an all-electric car. The drive control method aim at solving the problems that division of working modes during a finished automobile driving running is not considered, a torque compensation function is not considered in the running process of other vehicles except flooring of an accelerator pedal, and united efficiency of a power component is not considered in goal torque setting. The drive control method for the all-electric car comprises the steps of utilizing a finished automobile controller to automatically identify a finished automobile working mode according to current finished automobile acceleration mean values and an acceleration mean square errors, and enabling the finished automobile working mode to be one of a common mode, a power mode and an economic mode; working out an expected torque Treq under the corresponding mode according to a goal working mode control strategy in the finished automobile controller after the working mode identification is finished; restraining and correcting the expected torque Treq according to a power limiting value strategy in the finished automobile controller after the expected torque Treq under the goal working mode is obtained, and if a finished automobile has no major failure at the time, outputting ultimate goal torque commands to a motor.

The invention provides a fault early warning method of a wind generating set. The fault early warning method comprises the following steps of: 10) collecting the actual temperature value R and temperature related parameter data of a monitored point for N times in a sampling period; 20) inputting the collected actual temperature value R and the temperature related parameter data of the monitored point into a predetermined temperature mould, computing to obtain a temperature predicted value of the monitored point and taking the temperature predicted value as the theoretical temperature value P of the monitored point; 30) obtaining a temperature deviation DEV, a temperature mean-square deviation MSE and related coefficients SCC of the theoretical temperature value P and the actual temperature value; and 40) estimating the health condition of the wind generating set on the basis of the temperature deviation DEV, the temperature mean-square deviation MSE and related coefficients SCC. By means of the fault early warning method, the accuracy of estimating the health condition of the wind generating set can be improved.

The invention discloses a reconstruction method of sparse signal, mainly solving the problem of low rate of raw sparse signal reconstructed from observation vectors. Utilizing the decomposability of aconstrained object function, the method decomposes the problem of optimizing the constrained object function into a series of small constrained object functions for optimization to improve the reconstruction rate, comprising a raw data acquisition part, a raw sparse signal reconstruction part and a reconstruction accuracy evaluation part, wherein the raw data acquisition part comprises raw sparsesignal generation, matrix observation and vector observation; the raw sparse signal reconstruction part mainly comprises setting unconstrained object function, deducing constrained object function, decomposing the constrained object function by a sequential minimal optimization method, calculating reconstruction signal and debiasing reconstruction signal; the reconstruction accuracy evaluation isto compare the magnitude of the error of mean square. The reconstruction method can improve the reconstruction rate on the premise of ensuring reconstruction accuracy rate and be used for solving theproblem of sparse signal reconstruction in the fields of compressed sensing and the like.

The invention discloses a multi-band structure self-adaptive filter switching method for AEC (acoustic echo cancellation). Firstly, a far-end voice signal is acquired; a voice endpoint is detected, and a VAD (voice activity detection) flag bit and an improved envelope decision threshold are output; the voice signal is fed into a loudspeaker to serve as a desired signal and also input into a self-adaptive filter; the self-adaptive filter adopts a switchable multi-band structure and a corresponding self-adaptive algorithm, parameters of the filter are adjusted by use of the least mean square criterion according to feedback information, and the optimal solution is obtained. According to the provided switching method, voice characteristics are considered sufficiently under the condition that steady maladjustment is guaranteed, and optimized configuration of the convergence rate and the algorithm complexity is realized while advantages of the algorithm in the convergence rate are utilized. During actual application of echo cancellation, a single algorithm does not easily meet various variable demands. The variable switching algorithm provides more probability for a user and has great significance in application of self-adaptive echo cancellation.

Methods of estimating the signal-to-noise ratio (SNR) of a signal in an orthogonal frequency division multiplexed (OFDM) system include the steps of representing the signal as a complex symbol and rotating the complex symbol in a complex plane so that the signal component of the function lies substantially on the real axis of the complex plane and the noise function lies substantially on the imaginary axis of the complex plane. By obtaining the means squared value of the complex symbol and the variance of the complex symbol and dividing them, an estimate for the SNR of the signal is obtained.

A three dimensional area of quiet is created by an active noise cancellation system comprising a reference microphone receiving background noise and sending the noise signal to an adaptive active noise canceller. An adaptive filter system using weights updated by a least mean squares method or other method generates an anti-phase signal which is broadcasted to counteract the background noise. The resulting residual noise or residual signal is sent back to the adaptive active noise canceller to reset the weights of the adaptive filter.

The invention provides a voice detection method under noise condition, and belongs to the technical fields of digital signal processing, computer artificial intelligence and pattern recognition. The method comprises the following steps of: converting input signals to a frequency domain, and dividing into subbands; calculating a power spectrum of each subband to form a subband power spectrum; calculating mean-square deviation of the subband power spectrum of each frame, and comparing the mean-square deviation serving as a detection characteristic with an adaptive voice detection threshold to determine whether the current frame contains voice signals; and according to a detection result, adopting a certain endpoint determination strategy to determine an initial position and an ending position of a voice segment.

Multipath delay estimation of a direct sequence spread spectrum (DS-SS) signal transmitted in a multipath fading channel is accomplished by measuring the envelope of the signal to determine a new delay estimate. Delay estimates are also obtained in ray strength order, by subtracting out the influence of the stronger rays on the weaker ones. This subtraction approach can be performed iteratively, allowing further refinement of the delay estimates. Delay estimates can also be determined by minimizing the mean square error (MSE) between a measured correlation function and a modeled correlation function. The minimum mean square error (MMSE) approach can performed iteratively, to further refine the delay estimates. Maximum likelihood (ML) delay estimates can also be obtained by exploiting side information regarding the transmit and receive pulse shapes.

The invention relates to a topology control method for wireless sensor network based on uneven cluster, belong to sensor technical field, comprising: during the topology generating stage, introducing an uneven minimum mean square subtraction clustering mechanism on a finished cluster in order to reduce energy consumption of in-cluster node; using a strategy based on cluster head energy consumption for setting cluster head changing time, in order to equalize energy consumption on each cluster head node in the network; establishing a cluster head-cluster head energy sensing route, in order to avoid remote wireless transmission; during topology maintenance stage, using a cluster head selection scheme based on node surplus energy and in-cluster node distribution, and using the same strategy to set cluster changing time. With the realization of the method, it can reduce total network energy consumption and equalize energy consumption on each node, in order to prolong cooperative working time of most nodes in the network.

The invention provides a temporal-spatial joint filtering high-resolution DOA (Direction of Arrival) estimation method based on a compressed sensing technology. The method comprises the following steps: (1) acoustic pressure vibration velocity joint temporal filtering, to be specific, carrying out rotating combination on the data of an acoustic vector sensor, and utilizing differences in the corresponding properties of a signal and noise to carry out denoising processing; (2) matrix spatial filtering, to be specific, carrying out spatial filtering on the temporally filtered data by a matrix spatial filter of which the maximum value of the mean square error of attenuation in a stop-band and a passband is minimum; and (3) compressed sensing DOA estimation by the array of the acoustic vector sensor, to be specific, receiving data and a manually formed spatial over-complete redundance dictionary via an input array preprocessed by temporal filtering, and seeking the sparse representation of the signal to carry out vector spatial spectrum estimation. The method has great spectral resolution capability in the high-resolution DOA estimation problem of a high-speed motion target under single snapshot conditions and is insensitive to the wideband and narrowband properties and coherent properties of the signal.

The invention discloses a rolling bearing fault feature extraction method based on the signal sparse representation theory, and the method comprises the following steps: constructing an over-complete dictionary representing local damages of a rolling bearing through employing a multi-stage inherent frequency unit impulse response function; recognizing the multi-stage inherent frequency and damping ratio of the rolling bearing and a sensor system from a vibration response signal through a related filtering method, and obtaining an optimized dictionary; solving a sparse coefficient through employing a matching tracking algorithm, and improving the solving speed and precision through reasonable segmentation; reconstructing an impact response signal of each segment, and obtaining the sparse representation of a fault feature signal; carrying out time domain index statistic characteristic analysis of time intervals of adjacent impact response components in a sparse signal, and diagnosing the type of a fault through combining a mean value and a mean square deviation value. The method has the advantages of an analytical method and an adaptive method, improves the precision of waveform features, and can iron out the defects that a conventional method based on Fourier transform is not suitable for rotating speed fluctuation.