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Continuous information forecasting method based on filter

A prediction method and filter technology, applied in instruments, character and pattern recognition, computer components, etc., can solve problems such as increasing the burden of CPU and memory, and limiting the scope of MPS use.

Inactive Publication Date: 2010-06-09
SHANGHAI SECOND POLYTECHNIC UNIVERSITY
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AI Technical Summary

Problems solved by technology

Assuming that the original MPS method can be applied to continuous variables, it will be divided into multiple independent state values, which will greatly increase the burden on CPU and memory, which greatly limits the scope of use of MPS, making MPS only suitable for discrete Informative Prediction of Type Variables

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  • Continuous information forecasting method based on filter
  • Continuous information forecasting method based on filter
  • Continuous information forecasting method based on filter

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Embodiment Construction

[0088] based on the following Figure 5 to Figure 19 , specify the preferred embodiment of the present invention:

[0089] Figure 5 Indicates that a partial pattern can be scanned with a filter of 15×15 pixels, and the "filter score" of the partial pattern can be obtained, and this value will be assigned to the center position of the pattern.

[0090] Image 6 It is a schematic diagram of a two-dimensional "filter score" space divided by the "two-step division method". The equal fraction M=3 divided in the first step of division is represented by a solid line; the division of the second step is represented by a dotted line, at this time c min = 4,c max = 8 (the maximum number of patterns in the scoring class is c max , the minimum pattern number is c min ). Each score point corresponds to a local pattern in a training image, represented by a black solid point. S 1 and S 2 denote the maximum value of the two filter scores, respectively.

[0091] Figure 7 with Fi...

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Abstract

The invention discloses a continuous information forecasting method based on a filter, comprising the following steps: on the basis of multipoint geostatistical method, a filter is utilized to realize the dimensionality reduction of training images, filter score spaces are generated by the filter, all training patterns having similar filter scores are classified into a category in the filter score spaces, training patterns belonging to the same category are extracted in a random manner in the forecasting process, and then the patterns are pasted in an area to be stimulated. In the invention, the method is applicable to the reappearance of the structure feature information of the training images and has better effect in predicting continuous variables.

Description

technical field [0001] The invention relates to a filter-based continuous information prediction method, which can be widely used in many scientific fields such as medicine, geology, meteorology and mining. Background technique [0002] Information prediction plays an important role in many fields, such as medicine, geology, and mining. Interpolation methods are widely used for information prediction. The interpolation methods are mainly divided into two categories: "deterministic" interpolation methods and "uncertain" interpolation methods. The interpolation form, interpolation function parameters and interpolation results of the "deterministic" interpolation method are basically deterministic. The method mainly includes: the inverse distance weighting method, the basis function method and the method based on triangular mesh. "Uncertainty" The "uncertainty" of the interpolation method is reflected in the randomness of the selected interpolation form on the one hand, and ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
Inventor 杜奕张挺
Owner SHANGHAI SECOND POLYTECHNIC UNIVERSITY
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