Method for automatic structuring of computer codes adequate for processed information

FIELD: computer science.

SUBSTANCE: method includes performing a block of operations along N1 channels, where N1 is selected from 1 to 2256, wherein received information is separated on logically finished fragments, encoded on basis of preset algorithm, to produce a block of N-dimensional sets adequate for converted source information Aj with elements like {Bm, X1, X2,...,Xn}, where j - order number of set in range from 1 to 2256, Bm - identifier, X1-Xn - coordinate of element from its coordinates center, m and n are selected from 1 to 2256; received block of sets is compared to already accumulated and/or newly produced sets from multiple channels, intersecting portions of sets are found and cut out; after that cut intersections and sets remaining after cutting are distributed among databases, placing each same set into database appropriate for it and each of sets different with some parameter to databases appropriate for them and identifiers of databases storing these sets are substituted in place of cut sets.

EFFECT: higher speed of operation, higher precision, lower costs, broader functional capabilities, higher efficiency.

9 dwg

 

The technical field

The invention relates to the field of computer technology and can be used for automatic structuring of computer codes that are adequate to the processed information.

Prior art

A known method of automatic structuring of computer codes that are adequate to the processed information, including the selection of the volume flowing per unit time information part thereof, which is selected depending on the kinds of information, such as numeric or text, split the received information to logically complete the fragments that encode the received pieces of information and distribute them through the databases [Ailamazyan A.K., Stas E.V. "Informatics and theory development." M., Nauka, 1989].

Also known a method of automatic structuring of computer codes that are adequate to the processed information, including the selection of the volume flowing per unit time information part thereof, which is selected depending on the kinds of information, such as digital and/or text and/or graphics, split the received information to logically complete the fragments that encode the received pieces of information, transforming them according to the specified algorithm, the resulting set of transformed fragments distributed databases, placing each of the fragments sootvetstvuushuu him base [Daibetes, Century-Man den Berg, Dvud. Neural networks and the financial markets, M:Publishing house NT, 1977].

The disadvantages of the known methods are imperfect processing computer codes, adequate baseline information, and the relatively low speed of structuring computer codes.

Task and achieved technical result

Solved by the invention challenge is to improve methods of automatic structuring of computer codes that are adequate to the processed information, with achievement of the technical result in relation to, in particular, increase the speed of structuring computer codes. Using General method for automatic structuring of computer codes that are adequate to the processed information, makes it possible to save the consumption of computing resources (memory, number of operations of the processor and so on), to improve the speed and accuracy of structuring computer codes.

Summary of the invention

As a quick information disclosing the invention, it should be noted that the technical result achieved provide with the help of the proposed method of automatic structuring of computer codes that are adequate to the processed information, which includes the set of operations carried out by N1here is Alam, where N1choose from 1 to 2256. In each of N2channels, select the number that satisfies the inequality 1+1/N1(N21N1)/N12,3, where α1experimental factor selected depending on the type of information and the number of sources of its revenues in the range from 0.61≤ α11,3, extracted from volume V1arriving per unit of time information is part of volume V2which is selected from a ratio in the range of 0.56≤ (V22V1)/V12,8, where α2experimental factor selected depending on the kinds of information ranging from 0.56 to≤ α21,8. Break received information into logically complete parts, volumes V3ipreferred ratio is in the range of 0.45≤ (V3i3V2)/V22,7, where α3experimental factor selected depending on the characteristics of their split within from 0.45≤ α31,7, and i choose within 1≤ i≤ 2256.

Then encode the received pieces of information, transforming them according to a predetermined algorithm to obtain the aggregate N-dimensional sets adequate to transform the source information is. Andjelements of the form {mX1, X2,..., Xn}, where j is the sequence number set in the range from 1 to 2256InmID, X1-Xn- coordinate of an element relative to the origin of the element, a, m and n are chosen in the range from 1 to 2256. The resulting set of N-dimensional sets match in with existing sets and/or with new entrants sets through different channels, determine and cut the intersecting portions of the sets. Then cut the intersection of and remaining after the cutting of many distributed databases, placing each of the same sets in the corresponding database, and each distinguished by some parameter sets corresponding to these kinds of sets of the database and put into place the cut sets of the identifiers of storing these multiple databases.

List of drawings

Figure 1. The layout of the computer codes that are adequate to the processed information. Figure 2. A simplified diagram of the method for a single channel. Figure 3. A simplified diagram of the method for two channels. Figure 4. A simplified diagram of the method for ten channels. Figure 5. A detailed illustration of the claimed method. 6. Fragment of a detailed illustration of the claimed method.

Detailed description and primaryselection inventions

When presenting information, confirming the possibility of carrying out the invention, it is useful to describe in more detail the proposed method of automatic structuring of computer codes that are adequate to the processed information, which description is inappropriate to dwell on the well-known from the published data the implementation of its operations. This would be appropriate for the convenience of perceiving information definitions of the terms used.

Computer code - machineprecision representation of some piece of information (the original), in particular in the form of electromagnetic signals.

The criterion is a factor, which recognizes, for example, coordinate, Boolean condition, etc.

The system of criteria is a set of criteria related to the target orientation, in particular their suitability for use in the recognition process.

The memory functional unit means the implementation of the method, the retainer for a fixed term process information, with the possibility of its further reproduction, reading and other uses.

The specified algorithm is a set of rules that convert received by each channel of the source information.

Many - integration opredeleniya distinguish objects, who are called elements formed by them many [″ Handbook of mathematics″ , Ingebrigsten, K.semendyaev, ed. ″ Science″ , Moscow, 1986. S. 380. p].

Distinguish an object - computer codes that correspond to pieces of information.

The intersection of two sets Andjand Aj+k- this set, which consists of elements belonging to each of the sets Ajand Aj+k[″ Handbook of mathematics″ , Ingebrigsten, K.semendyaev, ed. ″ Nauka, Moscow, 1986, C, p], where j and j+k are the numbers of sets taken from region 1 to 2256or, by analogy, the intersection of any number of structured according to the claimed method sets.

Further detail it is appropriate to focus only on distinguishing the essential features of the operations of the proposed method lies in the fact. the method includes the set of operations carried out by N1channels, where N1choose from 1 to 2256. Selecting a specified number of channels in the claimed limits provides virtually all the present needs of the method. In each of N2channels, select the number that satisfies the inequality 1+1/N1(N21N1)/N12,3, where α1 experimental factor selected depending on the type of information and the number of sources of its revenues in the range from 0.61≤ α11,3, extracted from volume V1arriving per unit of time information is part of volume V2which is selected from a ratio in the range of 0.56≤ (V22V1)/V12,8, where α2experimental factor selected depending on the kinds of information ranging from 0.56 to≤ α21,8. In practice, this can be the variety of digital, textual, symbolic, graphical and multimodal information. The received information is divided into logically complete parts, volumes V3ipreferred ratio is in the range of 0.45≤ (V3i3V2)/V22,7, where α3experimental factor selected depending on the characteristics of their split within from 0.45≤ α31,7, and i choose within 1≤ i≤ 2256. Among the simplest features split the received information into logically complete fragments, you can specify, for example, equal volumes of fragments, or is not equal to its crash.

Then encode the received pieces of information, transforming them according to a predetermined algorithm to obtain sosaku the particular N-dimensional sets, adequate convertible to the original information, Ajelements (and/or frames) {m, X1, X2,..., Xn), where j is the sequence number set in the range from 1 to 2256InmID, X1-Xn- coordinate of an element relative to the origin of the element, a, m and n are chosen in the range from 1 to 2256. Here it is expedient to note that these elements are often referred to as frames, and each element has its own coordinate system. The resulting set of N-dimensional sets match in with existing sets and/or with new entrants sets through different channels, determine and cut the intersecting portions of the sets. Comparison with existing sets and/or with new entrants are performed simultaneously or sequentially in time. Then cut the intersection of and remaining after the cutting of many distributed databases, placing each of the same sets in the corresponding database, and each of them differ in some parameter sets corresponding to these kinds of sets of the database and put into place the cut sets of the identifiers of storing these multiple databases.

Given the use of a number of analytical ratios, it should be noted that for the practical implementation of sets, UD is vitoriosa analytical correlations between parameter values in the declared limits - choose settings, for example, N, N1or N2is the whole positive natural numbers, and for the rest of the parameters are real numbers, excluding irrational, transcendental, complex, negative, and other technically incorrect or practically not applicable, or not reproducible values of related parameters.

Industrial applicability and the achievement of the technical result

The criterion of industrial applicability of the claimed subject matter proves to be a wide acceptance and use of the described techniques of computer technologies on a massive scale, and the absence of the stated claims of any practically difficult-to-implement features. Technical result achieved, as shown by experimental data, can only be realized interrelated set of all essential features of the claimed method, reflected in the claims. For example, searching for the words ″ Example″ in unsorted, non-indexed database of 100 million records or from 100 billion records the number of operations will be approximately the same, i.e., the search speed will be the highest in comparison with known methods under adequate conditions of their use, depends only on the length of the query and very weakly depends on the size of the and the database.

The lower and upper values of the declared limits were derived on the basis of statistical processing of experimental results, analysis and synthesis and their known from published data sources, as well as inventive intuition, based on the conditions of achievement of the technical result. Specified in the claims differences provide a basis to conclude that the novelty of this technical solution, but a combination of the requested claims about its inventive step, which is proved as above detailed description of the declared objects and the following description of examples of the practical implementation of the inventive method. For this purpose it is expedient to provide the basic functional diagram of the method of automatic structuring of computer codes that are adequate to the processed information, when creating a database.

Conversion of computer codes that are adequate to the processed information, the proposed method can partly be explained by means Figa), which reflects the case, when receiving the first set, schematically shown as oval 1. Because the shared database is still empty, then the set fits into the new database DB No. 1 data. Figb) reflects the case when there are another two sets 2 and 4 containing cell battery (included) matching is you. The intersection of the sets of 3 is cut out and placed in the appropriate database No. 3, his place in sets 2 and 4 is inserted into the ID database No. 3, modified sets 2 and 4 are placed in respective databases of the DB 3 and the DB No. 4.

Figv) reflects the case when you receive the next set of N-1 that does not contain any matching item with the previous sets, so the set of N-1 is placed in a new database DB-No. N-1. Figg) reflects the case when you receive the next set N containing the entire matching items with multiple N-1, Christmastime in the database DB # N-1. The intersection of the sets N is cut and placed and the appropriate database DB # N, in the set of N-1 is inserted into the database ID DB # N, respectively, changes the database DB # N-1. Thus, in each separate database DB contains many that do not have matching entries, i.e. none of the sets do not intersect.

Simplified schematic of the method consistently for one, two and 10 channels are shown respectively on figure 2, figure 3 and Figure 4. Figure 2 schematically depicts a structured database of textual information that is used to store large amounts of textual information with the selection of one channel of textual information.

Figure 3 schematically depicts the structured is consistent database of textual and graphical information, designed to store large amounts of text and graphic information with the choice of two channels - one for the text information, the second graphic information.

In detail it is advisable to describe a structured database of textual, graphical and audio information that is used to store large amounts of text, graphic and audio information simultaneously on 10 channels (Figure 4), for example, 6 text, 2 graphics and 2 audio. The set of operations of a method implemented in the device of Figure 4, can be characterized as follows: N1is chosen equal to 10, N2- from 2 to 6 α1=1 for text information, α1=0.9 for graphic information, α1=1.1 for audio information. Extracted from volume V1=10 000 KB/s arriving per unit of time information is part of volume V2=1000 KB/s α2=1 for text information, α2=0.8 for graphic information, α2=1,2 for audio information. Break received information into logically complete parts, volumes are chosen in the ratio of 1.4≤ (V3i3V2)/V21,6, where α3=1 for text information, α3=0.5 for graphic information, α3=1.7 for sound information and, and i choose within 1≤ i≤ 220.

Encode the received pieces of information, transforming them according to a predetermined algorithm to obtain the aggregate N-dimensional sets Andjelements of the form {VM, X1X2,... Xn}, where amID, X1-Xn- coordinate element, aj- the sequence number set in the range from 1 to 263regarding the origin of the element (each element has its own coordinate system)is adequate to convert the original data, where m and n are chosen in the range from 1 to 263. The resulting set of N-dimensional sets match in with existing sets and/or with new entrants (simultaneously or sequentially in time) set to different channels, isolated and cut the intersecting portions of the sets, then cut sets intersections and remaining after the cutting of many distributed databases, placing each of the same sets in the corresponding database, and each distinguished by some parameter sets corresponding to these kinds of sets of the database and put into place the cut sets of the identifiers of storing these multiple databases.

Experimentally this was obtained speed automatic structuring of computer codes, adequately processed the information, equal 930,55 KB/s on a computing device with a Quad-processor Pentium III 800MHz, RAM 1024 MB.

To illustrate the inventive method in example 5 used a structured database of textual information. This database is designed to store large amounts of textual information. In the process of implementing the inventive method is chosen (Figure 5, operation choose depicted by the arrow 1) number of channels (Ref. 2) N1equal to 1, N2=1 if α1=1, which transmit volume V1(Figure 5, item 3) information. Allocate (Figure 5, operation allocate depicted by the arrow denoted by the position of 4) of volume V1=100 KB/s arriving per unit time information part (Figure 5. position 5) volume V1=8 b/s, i.e. in this case V2is a piece of textual information, for example, the word ″ argument″, α2=0,9.

Then break (Figure 5, Ref. 6) the received information to logically complete fragments (Figure 5, Ref. 7), the volume of which is chosen in the range of 1.3≤ (V3(i)3V2)/V21,5, where α3=1, a i choose within 1≤ i≤ 23. The result is the following defined using the above analytical expressions specific values for volumes of fragments 7: V3(1)=1 b/s, V3(2) =1 b/s, V3(3)=1 b/s, V3(4)=1 b/s, V3(5)=1 b/s, V3(6)=1 b/s, V3(7)=1 b/s, V3(8)=1 b/s Selected specific values logically complete fragments 7 encode (Figure 5, Ref. 8), transforming them according to the specified algorithm, in particular for this example, y=f(x), where f(x)=V3(i)-191, to obtain lookupnode N-dimensional sets Aj(POS. 9) elements of ak(POS. 10) of the form {m, X1X2,..., Xn}, where BmID, X1-Xn- coordinate element, where j is the sequence number set in the range from 1 to 23, 1≤ k≤ 23regarding the origin of the element (each element of akhas its own coordinate system)is adequate to convert the original data, where m and n are chosen in the range from 1 to 231.

The result is the converted items in this particular case types and1={1, 1}, and2={2, 2}, and3={3, 3}, a4={4, 4}, and5={5, 5}, and6={2, 6}, and7={6, 7}, and8={7, 8}. When this individual identifiers (the first digits in brackets) of elements of the sets can be the same in the case of conversions of the pieces of information for a given algorithm. Further, the set of operations performed as a single unit (Figure 5. POS. 11). The resulting set of N-dimensional sets 9 map (Figure 5. item 12) with existing sets the mi (for example, the database 13 (DB No. 1)) and/or with new entrants (simultaneously or sequentially in time) sets 14 and 15 through different channels. Identify and cut out (Fig.6, item 16) intersecting portions of the sets 17 and 18. Then cut the intersection of (Fig.6, item 19) and remaining after the cut set is replaced with the parts distributed (Figure 5. item 19) databases, placing each of the same sets in the corresponding database, and each distinguished by some parameter sets corresponding to these kinds of sets of the database and placed (Figure 5, item 20 or 6, item 20) to the place of the cut sets identifiers storing these multiple databases.

The result (Figure 5, item 21) shared database, consisting of hierarchically related databases - each child database is represented by a unique identifier in the corresponding parent databases.

Experimentally this was obtained speed automatic structuring of computer codes that are adequate to the processed information, 96 KB/s on a computing device with a single processor Pentium III 800MHz, RAM 256 MB.

In addition to the above technical result of the practical implementation of the claimed subject matter can significantly extend the possibility of the activity of its use as applied, for example, to different types and amounts of incoming information, provides an additional opportunity for efficient hardware implementation (price/quality/speed) using various types of hardware components, as well as the automatic adaptation under decision of tasks of different types, in contrast to neural networks, which require a predetermined topology for each specific task.

A method of automatic structuring of computer codes in the form of electromagnetic signals, adequate processing information comprising a set of operations which is performed for N1channels, where N1automatically select from 1 to 2256thus, in each of the N2channels, automatically selected in the number satisfying the inequality 1+1/N1(N21N1)/N12,3, where α1experimental factor that is automatically selected depending on the kind of information presented in the form of computer codes that are adequate to the processed information, and the number of sources of income within 0,61≤ α11,3, automatically extracted from volume V1arriving per unit of time of the information presented in the form of computer codes that are adequate to the processed information, h is the terrain of volume V 2that is automatically selected from a ratio in the range of 0.56≤ (V22V1)/V12,8, where α2experimental factor that is automatically selected depending on the kind of information presented in the form of computer codes that are adequate to the processed information, within 0.56≤ α21,8, automatically split the received information, presented in the form of computer codes, adequately processed information into logically complete parts, volumes V3iwhich is automatically selected from a ratio in the range of 0.45≤ (V3i3V2)/V22,7, where α3experimental factor that is automatically selected depending on the characteristics of their split within 0,45≤ α31,7, and i automatically choose within 1≤ i≤ 2256automatically encode the received pieces of information, presented in the form of computer codes that are adequate to the processed information, automatically converting them to a predetermined algorithm to obtain the aggregate N-dimensional sets containing computer codes that are adequate to transform the source information, Ajelements of the form {mX1X2,..., Xn}, where j is the ordinal number of sets in p is adelah from 1 to 2 256InmID, X1-Xn- coordinate of an element relative to the origin of the element, and m and n are automatically chosen in the range from 1 to 2256received the set of N-dimensional sets automatically match in with existing sets and/or automatically with the newly received set on different channels, automatically detect and automatically cut the intersecting portions of the sets, then cut sets intersections and remaining after the cut set automatically distributed databases, automatically placing each of the same sets in the corresponding database, and each distinguished by some parameter sets in these types of sets, database, and automatically put into place the cut sets of the identifiers of storing these multiple databases containing computer code, adequately processed information.



 

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