31 results about "Transformation operator" patented technology

A method for the three-dimensional imaging of a sample in which image information from different depth planes of the sample is stored in a spatially resolved manner, and the three-dimensional image of the sample is subsequently reconstructed from this stored image information is provided. A reference structure is applied to the illumination light, at least one fluorescing reference object is positioned next to or in the sample, images of the reference structure of the illumination light, of the reference object are recorded from at least one detection direction and evaluated. The light sheet is brought into an optimal position based on the results and image information of the reference object and of the sample from a plurality of detection directions is stored. Transformation operators are obtained on the basis of the stored image information and the reconstruction of the three-dimensional image of the is based on these transformation operators.

An apparatus for compressing an image data with an array of pixels comprising a data length is disclosed. The apparatus comprises a rearranging unit, a transformation operator, a quantizer and a coding operator. The rearranging unit is configured to transform the array to form a rearranged block with a mark value. The transformation operator is configured to obtain transform coefficients of the rearranged block according to a predetermined transformation. The quantizer is configured to quantize the transform coefficients. The coding operator is configured to generate a result data by coding the transform coefficients which is quantized and the mark value according to a predetermined coding method.

A method for iterative derivation of a master image from sampled images of non-identical, at least partially overlapping, regions of a scene. The method includes defining a transformation operator mapping positions within the master image to corresponding positions in the sampled image; a distortion operator simulating a modulation transfer function associated with an imaging sensor from which the sampled image was generated; and a sampling operator for reducing an image from the output resolution to the resolution of the sampled image. For each sampled image the transformation operator, distortion operator and sampling operator are applied to a current master image hypothesis to generate a predicted image A difference image is calculated which has pixel values corresponding to the difference in corresponding pixel values between the sampled image and the predicted image. A back-projection of each of the difference images is performed to generate a correction image for the current master image hypothesis. Finally, the correction images are employed to perform a correction to the current master image hypothesis to generate a new master image hypothesis. The correction to the current master image hypothesis includes combining the correction images by deriving a weighted average of values of corresponding pixels in the correction images. The weight of each pixel in each correction image is calculated as a function of a distance as measured in the sampled image between: a point in the sampled image to which the pixel in the correction image is mapped by the transformation operator, and at least one pixel centroid proximal to that point.

A system for the dynamic encoding in a semantic network of both syntactic and semantic information into a common four valued logical notation. The encoding of new information being benign to prior syntactic constructions, tests for N conditionals in time 0(C) and allows for the proper quantification of variables at each recursive step. The query / inference engine constructed from such an implementation is able to optimize short term memory for maximizing long term storage in the automaton. In a parallel context this can be viewed as optimizing communication and memory allocation between processes. The self-referencing system is capable of analogically extending knowledge from one knowledge source to another linearly. Disclosed embodiments include machine translation, text summarization, natural language speech recognition natural language.

The invention discloses a quick sparse Radon transformation method based on iterative shrinkage. The quick sparse Radon transformation method comprises the following steps: firstly, setting an initial variable value; secondly, constructing a transformation operator L and calculating generalized inverse (LTL)-1LT of the transformation operator L; thirdly, treating a seismic channel set d to be treated by utilizing the generalized inverse (LTL)-1LT of the transformation operator L; and lastly, judging if all channel sets in a seismic data cube are treated, if not, continuing to treat the seismic channel set d to be treated by utilizing the generalized inverse (LTL)-1LT of the transformation operator L, and if so, ending. According to the quick sparse Radon transformation method, for one seismic data cube collected by adopting the same collection parameters, the generalized inverse of the transformation operator L only needs to be calculated once, then the transformation operator L and the generalized inverse (LTL)-1LT of the transformation operator L are applied to all seismic channel sets, thereby greatly reducing calculated amount; and the iterative shrinkage algorithm only includes product operation of simple matrixes and vectors and threshold operation, greatly reduces the calculated amount relative to the conventional sparse Radon transformation, and better adapts to treatment of practical seismic data.

The invention discloses a method for restricting configuration modification and software upgrade of terminal equipment, which is applied to a network side management unit and terminal equipment, including: the management unit acquires terminal identification information; the management unit automatically generates a password according to the identification information , the password is calculated and generated according to the encryption algorithm and the identification information; the management unit initiates a login request to the terminal device, and sends the password to the terminal device; the terminal device receives the login request and the password; the terminal device calculates and verifies the correctness of the password, and if the verification is passed, the terminal device grants the login user the authority to modify the configuration and upgrade the software of the terminal device. The invention also discloses a system for realizing the method of the invention. The present invention can effectively restrict configuration modification and software upgrade of terminal equipment, and improve security; it can be used to prevent equipment from switching networks, reduce loss of operator assets, simplify operator terminal configuration and upgrade, and facilitate network expansion and transformation .

A system for the dynamic encoding in a semantic network of both syntactic and semantic information into a common four valued logical notation. The encoding of new information being benign to prior syntactic constructions, tests for N conditionals in time O(C) and allows for the proper quantification of variables at each recursive step. The query / inference engine constructed from such an implementation is able to optimize short term memory for maximizing long term storage in the automaton. In a parallel context this can be viewed as optimizing communication and memory allocation between processes. The self-referencing system is capable of analogically extending knowledge from one knowledge source to another linearly. Disclosed embodiments include machine translation, text summarization, natural language speech recognition natural language.

Sonic logging data including a sonic waveform associated with a plurality of shot gathers is accessed. A transformation operator is applied to the sonic logging data to provide a transformed sonic image, the transformation operator including at least one of a short time average long time average (STA / LTA) operator, a phase shift operator, and a deconvolution operator. A machine learning process is performed using the transformed sonic image to determine a sonic slowness associated with the sonic logging data. The sonic slowness is provided as an output.