6 results about "Distortion function" patented technology

The invention discloses a multi-parameter distortion compensation method for a fractured rock mass seepage similar model test, and relates to the technical field of rock mass engineering physical model tests. The method comprises the following steps of: firstly, determining two constraint conditions that the fluid property is invariable and the gravitational acceleration is invariable, correspondingly selecting a basic physical quantity and extracting a core criterion; then analyzing three types of distortion sources of geometric dimensions, dielectric materials and boundary conditions, and establishing a distortion function according to result parameters of seepage flow velocity, seepage flow and seepage pressure; secondly, parameters difficult to control are selected as distortion items, parameters easy to regulate and control are selected as compensation items, the distortion items are substituted into a distortion function to obtain a distortion ratio, the optimal distortion ratio of the compensation items is solved based on a compensation balance formula, and the parameters are adjusted; and finally verifying the interval range of the actually measured distortion ratio. According to the method, the multi-source distortion coupling influence is accurately quantified, the compensation pertinence and precision are improved, operation is easy and convenient, universality is high, and reliable support is provided for underground engineering seepage research.

The economic tolerance analysis method, device, equipment and storage medium of the optical system provided by the embodiment of the application first determine the parameter tolerance of the structure to be analyzed, then determine the distortion function based on the parameter tolerance and use the Taylor formula to determine the change of the distortion when the parameter tolerance changes; then determine the sensitivity coefficient based on the object side of the optical system to solve the sensitivity coefficient in the Taylor formula expansion, so as to determine the parameters that have a great influence on the distortion according to the size of the sensitivity coefficient; finally, determine the best economic tolerance according to the tolerance cost function corresponding to each parameter tolerance, the sensitivity coefficient and the distortion function determined according to the preset processing parameter information, so as to solve the distortion expression and the tolerance cost function determined in the above steps, and determine the size of the parameter tolerance, so that the tolerance value can meet the distortion requirement and the processing cost is the lowest, and the purpose of balancing the economic tolerance is achieved.

A sensing method and apparatus. The method comprises: a first device inputting first compressed information into a decompression model, so as to obtain second sensing information output by the decompression model, wherein the first compressed information is related to first sensing information, the first sensing information comprises information that indicates first power corresponding to at least one spatial position, and the second sensing information comprises information that indicates second power corresponding to the at least one spatial position; and on the basis of a loss function, the first device updating parameters of a compression model and / or the decompression model, wherein the loss function comprises a distortion function between the first sensing information and the second sensing information, the distortion function is related to a power difference corresponding to the at least one spatial position and the maximum first power indicated by the first sensing information, and the power difference corresponding to one of the at least one spatial position refers to the difference between the first power and the second power. The distortion function in the embodiments of the present application enables relatively accurate power recovery at a receiving end, thereby facilitating an improvement in sensing precision.

The invention discloses a sensing method and device. The first device inputs first compression information to the decompression model to obtain second sensing information output by the decompression model, the first compression information is related to first sensing information, and the first sensing information comprises information indicating first power corresponding to at least one spatial position; the second perception information comprises information indicating second power corresponding to at least one spatial position. The first equipment updates parameters of the compression model and / or the decompression model according to a loss function, the loss function comprises a distortion function between the first perception information and the second perception information, and the distortion function is related to a power difference value corresponding to at least one spatial position and the maximum first power indicated by the first perception information; the power difference value corresponding to one spatial position in the at least one spatial position refers to the difference value of the first power and the second power. According to the embodiment of the invention, the distortion function enables the power recovery of the receiving end to be more accurate, and facilitates the improvement of the sensing precision.

A method for correcting scan data generated by scanning a sample with charged particles and detecting signal charged particles emitted from the sample, the method including selecting at least one scan profile for scanning the sample; and correcting scan data generated by the scanning of the sample, based on at least one known distortion function f(x,y) associated with the at least one selected scan profile.

A digital pre-distortion circuit and technique for a signal being amplified. Digital pre-distortion is performed using a model-based pre-distortion function. Pre-distortion is further corrected using a data-driven pre-distortion function. The model-based pre-distortion function and the data-driven pre-distortion function are trained using training data including a digital loopback signal generated by sampling a loopback signal of an amplifier, the digital pre-distorted signal input to the amplifier for a time period, and an intermediate signal output from the model-based pre-distortion function driven by the digital loopback signal or an output of the data-driven pre-distortion function. Parameters may be continually updated in order to account for changes in characteristics of the amplifier.