726 results about "Random error" patented technology

The invention discloses a data validation, mirroring and error/erasure correction method for the dispersal and protection of one and two-dimensional data at the micro level for computer, communication and storage systems. Each of 256 possible 8-bit data bytes are mirrored with a unique 8-bit ECC byte. The ECC enables 8-bit burst and 4-bit random error detection plus 2-bit random error correction for each encoded data byte. With the data byte and ECC byte configured into a 4 bit×4 bit codeword array and dispersed in either row, column or both dimensions the method can perform dual 4-bit row and column erasure recovery. It is shown that for each codeword there are 12 possible combinations of row and column elements called couplets capable of mirroring the data byte. These byte level micro-mirrors outperform conventional mirroring in that each byte and its ECC mirror can self-detect and self-correct random errors and can recover all dual erasure combinations over four elements. Encoding at the byte quanta level maximizes application flexibility. Also disclosed are fast encode, decode and reconstruction methods via boolean logic, processor instructions and software table look-up with the intent to run at line and application speeds. The new error control method can augment ARQ algorithms and bring resiliency to system fabrics including routers and links previously limited to the recovery of transient errors. Image storage and storage over arrays of static devices can benefit from the two-dimensional capabilities. Applications with critical data integrity requirements can utilize the method for end-to-end protection and validation. An extra ECC byte per codeword extends both the resiliency and dimensionality.

A temperature compensation method for denoising a fiber-optic gyroscope on the basis of time series analysis comprises four steps of: step 1, designing an experimental scheme, performing fixed point low and high temperature testing experiment on the fiber-optic gyroscope, and utilizing acquisition software for data acquisition; step 2, performing time series analysis on the zero offset data of the gyroscope, and establishing the mathematical model of the random error of the fiber-optic gyroscope; step 3, adopting a kalman filtering algorithm to filter random noise in the zero offset data of the fiber-optic gyroscope; and step 4, utilizing the data which is de-noised by the kalman filtering to identify the model structure of the temperature shift error of the fiber-optic gyroscope, and calculating the parameters of the identified model. The method establishes the multinomial model of the static temperature shift error of the fiber-optic gyroscope through time series analysis, kalman filtering denoising treatment and identification of the temperature shift error model structure and parameters. The method completely meets the real-time compensation requirement on the project, and has a better practicable value and a wide application prospect in the technical field of aerospace navigation.

At Step 602, the grid of a wafer loaded into an exposure apparatus is approximated by a mathematical function fitting up to, for example, a cubic function, and at Step 612, the magnitude of a residual error between the position of a sample shot area obtained by the function and an actually measured position is compared with a predetermined threshold value. GCM measurement is performed in a mathematical function mode in a subroutine 616, or it is performed in a map mode in a subroutine 616, on the basis of the result of the comparison. In addition, it is determined whether to extract non-linear components from the wafer in each lot on the basis of a variation in the temperature of the wafer (Step 622) and a variation in random error between the wafers (Step 624).

The invention discloses a tunnel convergence monitoring method, which utilizes a measuring device to measure a tunnel section, inputs actually measured data to a computer so as to implement ellipse fitting processing, computes a fitted ellipse equation, determines the position of the section center, implements the elimination processing of parasitic error and random error of the measured data, computes the deformation degree of each measured point relative to the section center, and finally outputs a figure that is unfolded by taking the polar angle of the section center as horizontal axis to show the deformation degree of the tunnel section. The tunnel convergence monitoring method implements reasonable processing of the measured data of the tunnel section, can reflect the actual deformation situation of the tunnel section more veritably, and can be widely applied in the monitoring working of circular tunnel convergence.

A system and method identify hydrocarbon productive reservoir zones using Monte Carlo numerical analysis to account for uncertainties in log measurements and petrophysical parameters. Random errors in logging tool responses and core measurements, as well as reservoir heterogeneity, are incorporated in a Monte Carlo simulation to output appropriate petrophysical models to calculate statistical distributions for saturation and permeability to define productive zones, non-productive zones and zones of undetermined productivity as a basis of deciding whether additional logging, core sampling or well test data are needed to reclassify the undetermined zones as either productive or non-productive. As uncertainties are quantified in the analysis, the degree of certainty in determining productive and non-productive zones is known and can be used to decide whether to further test, stimulate or abandon reservoir zones.

The invention discloses a method for detecting mutation information in a multiplex amplification sequencing product of a genome. The method comprises steps as follows: sequencing data are subjected to quality assessment and preprocessing; a recognizable sequencing sequence is selected for sequence assembling; the recognizable sequencing sequence or a sequence obtained through assembling is compared with a reference gene sequence, and preliminary variation information is obtained; fine calibration of sequence variation is performed according to different types of conditions; a calibrated sequencing fragment is obtained; the homozygosis or heterozygosis state of a target fragment is obtained according to the type of the sequencing fragment with the highest abundance; finally, the mutation information in the multiplex amplification sequencing product of the genome is obtained. By means of the method, the amplification product can be rapidly, efficiently and accurately recognized, and the calculation resources are saved; the sequence assembling process is compatible, and the problem of reduction of the quality value of basic groups produced in the sequencing process can be effectively solved; the homozygosis/heterozygosis state of variation information can be more effectively and stably judged, and random errors introduced in the PCR (polymerase chain reaction) process and the sequencing process are eliminated.

The invention provides an MEMS (Micro-electromechanical Systems) gyroscope random error predication method based on a grey wavelet neural network. The predication method comprises the following steps: carrying out pretreatment on output data of an MEMS gyroscope, collecting the output data of the MEMS gyroscope, carrying out wavelet analysis on the output data, and selecting a Db4 wavelet function so as to carry out de-noising processing on the output data of the gyroscope; grouping the output data of the MEMS gyroscope after de-noising processing, and determining an input vector and a target vector; building a grey wavelet network predication model, determining the input node number of the grey wavelet network, the outputting node number and the hidden layer node number, and initializing the network; training the built network, and storing the network for predicating the trend of gyroscope random error. Compared with a traditional gyroscope random error modeling method, according to the method, a grey theory is combined with the wavelet neural network, and thus the predication accuracy of the MEMS gyroscope random error is improved, and the predication accuracy is obviously improved compared with the traditional method.

Various edge detection arrangements are disclosed, including an edge detection method and arrangement that utilizes outputs of commonly illuminated reference and edge sensors as the inputs for a comparator. The reference sensor is configured to have a wide field of view and the edge sensor is configured to have a narrow, high gain, field of view. Therefore, the reference sensor has a broad signal response to an edge passage and the edge sensor a steep and narrow signal response. When the two signals are biased to cross each other, the comparator output changes state, indicating passage of an edge. Because the reference sensor provides a base signal level directly related to the real time illumination level that the edge sensor also receives, the reference sensor provides a switch point along the transition ramp of the edge sensor that integrates a majority of the random error sources.

The invention relates to a real-time on-line monitoring apparatus of blade vibration of a flue gas turbine. The monitoring apparatus comprises blade tip timing sensors, an angle reference sensor, a rotating speed synchronization sensor, a preprocessing system, a data integrated processing card, and a computer. The blade tip timing sensors, the angle reference sensor, and the rotating speed synchronization sensor are connected with the preprocessing system that is connected with the data integrated processing card; and the data integrated processing card is connected with the computer. According to the invention, the sensors employ double-shielded capacitance impulsers; single-core double-shielded wires are utilized as transmission lines of output signals; and a driving cable technology is utilized to effectively reduce a random error introduced by an environmental interference; and a charge amplification circuit is used to extract a capacitance pulse signal, thereby eliminating the system error basically and improving the measurement accuracy of the system.

System correcting random and/or burst errors using RS (Reed-Solomon) code, turbo/LDPC (Low Density Parity Check) code and convolutional interleave. A novel approach is presented that combines different coding types within a communication system to perform various types of error correction. This combination of accommodating different coding types may be employed at either end of a communication channel (e.g., at a transmitter end when performing encoding and/or at a receiver end when performing decoding). By combining different coding types within a communication system, the error correcting capabilities of the overall system is significantly improved. The appropriate combination of turbo code and/or LDPC code along with RS code allows for error correction or various error types including random error and burst error (or impulse noise).

The invention discloses a laser tracker-based machine tool error dynamic compensation method. A laser tracker is adopted to perform dynamic tracking detection; and the method is suitable for being used in laboratory environments with strictly controlled temperature and humidity and can also be used in workshop site environments with severer conditions. Laser interference ranging, photoelectric detection, precision machinery, a computer and a control and modern numerical value calculation theory are integrated by the laser tracker; a space moving object is tracked and spatial three-dimensional coordinates of an object are measured in real time; and the method has the characteristics of high precision, high efficiency, real-time tracking measurement, quickness and convenience in mounting, easiness in operation and the like. A machine tool is dynamically monitored and compensated in real time based on a laser tracker measurement result; error measured by using the scheme is total error obtained after all system errors and random error are superposed; and thus, all error values can be dynamically compensated in real time by the scheme, the system precision of the machine tool is greatly improved, and a detection device of the machine tool is simplified.

The invention discloses a zero-crossing-point accurate detection method for AC voltage signals. The method includes the following steps: firstly selecting a comparatively large hardware filtering time constant to ensure that harmonic waves and random noises which may be included in the AC voltage signals can be filtered comparatively well; using large-time-constant software PQ filtering to extract and eliminate DC drift generated by software and hardware; setting a software judgment advancing quantity so as to offset zero-crossing-point delay caused by hardware filtering; accurately calculating random errors t caused by sampling intervals; and at last, using capture and comparison functions of an embedded microcontroller to realize accurate information of an AC voltage frequency and phase so that accurate phase locking of the AC signals can be realized. The detection method solves a problem of zero drift and phase delay caused by a hardware detection circuit and a software algorithm when zero-crossing-point detection is carried out on the AC voltage signals.