Device for classification of digital signals order
 Statistical analyzer of quality and recording of electric power flow / 2260842Device has current input clamp and mating input clamp, current counter with inbuilt pulse sensor, converter of alternating voltage to direct voltage, analog=digital converter, register, digital memory block, pulse counter, selection pulse generator, second and first D-triggers, first, second and third and fourth AND elements, SR-trigger, OR element, clock pulse generator, pulse distributor. |
 Method for separating trend using method of sliding trend estimates multiplication of its single source realization and device for realization of said method / 2257610Device has physical value measurements results storage block, delay block, averaging-out block, control block, clock pulse generation block, block for approximation using method of least squares, block for storing trend estimates. |
 Method for identification of linearized dynamic object / 2256950On basis of discontinuous measurements of input x(t) and output y(t) signals of object with discretization step Δt ranges are determined according to formula: [x(nΔt)-εx,x(nΔt)+εx],[y(nΔt)-εy,y(Δt)+εy], where n=0, 1, 2,..., and εx, εy - values of limit allowed errors of used measurement means, interval values of input and output signals are sent to continuous division identifier, on which continuous division is produced with several interval coefficients, on basis of which interval discontinuous transfer function is restored and also predicting model, and interval model values of output object signal are determined. |
 Device for measuring two-dimensional distributions of random processes / 2253892Device has ADC, address multiplexer, adder, AND element, OR element, two memory blocks, quality control block, division block, indication block, count number counter, reverse counter, control block, quality control block. |
 Device for determining characteristics of a random process / 2253147Device has buffer memory register, pulse generator, switches, register, commutators, pulse counter, inversions number counter, comparison circuit, AND elements group, subtraction elements group, scale amplifiers group, adders group, delay elements groups, delay elements, cycles counter, OR elements group, reverse value computation blocks group, square-ware generators group. |
 Device for measuring distributions of random processes / 2249851Device has ADC, address multiplexer, memory block, combination adder, division block, counts number counter, control block, quality control block, indication block. |
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Device for measuring distributions of random processes / 2249851 Device has ADC, address multiplexer, memory block, combination adder, division block, counts number counter, control block, quality control block, indication block. |
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Device for determining characteristics of a random process / 2253147 Device has buffer memory register, pulse generator, switches, register, commutators, pulse counter, inversions number counter, comparison circuit, AND elements group, subtraction elements group, scale amplifiers group, adders group, delay elements groups, delay elements, cycles counter, OR elements group, reverse value computation blocks group, square-ware generators group. |
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Device for measuring two-dimensional distributions of random processes / 2253892 Device has ADC, address multiplexer, adder, AND element, OR element, two memory blocks, quality control block, division block, indication block, count number counter, reverse counter, control block, quality control block. |
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Method for identification of linearized dynamic object / 2256950 On basis of discontinuous measurements of input x(t) and output y(t) signals of object with discretization step Δt ranges are determined according to formula: [x(nΔt)-εx,x(nΔt)+εx],[y(nΔt)-εy,y(Δt)+εy], where n=0, 1, 2,..., and εx, εy - values of limit allowed errors of used measurement means, interval values of input and output signals are sent to continuous division identifier, on which continuous division is produced with several interval coefficients, on basis of which interval discontinuous transfer function is restored and also predicting model, and interval model values of output object signal are determined. |
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Method for separating trend using method of sliding trend estimates multiplication of its single source realization and device for realization of said method / 2257610 Device has physical value measurements results storage block, delay block, averaging-out block, control block, clock pulse generation block, block for approximation using method of least squares, block for storing trend estimates. |
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Statistical analyzer of quality and recording of electric power flow / 2260842 Device has current input clamp and mating input clamp, current counter with inbuilt pulse sensor, converter of alternating voltage to direct voltage, analog=digital converter, register, digital memory block, pulse counter, selection pulse generator, second and first D-triggers, first, second and third and fourth AND elements, SR-trigger, OR element, clock pulse generator, pulse distributor. |
 Device for classification of digital signals order / 2268485Device has analog-digital converter, two memory block, n comparators, decoder, n counters. |
 Probability device / 2276402Probability device contains indicator of random series 1, block for forming non-integer indicator values 2, correction block 3, block for forming values of matrix 4, control block 5, threshold devices block 6, block for forming indicator values 7, clock pulses generator 8, DENY element 9, AND elements block 10, memory block 11, decoder 12, time setting block 13, OR element 14, block 15 for increasing trustworthiness. Device makes it possible to model controllable semi-markov circuits with high trustworthiness with consideration of controlling effects, and dynamically changes threshold values of states, set both numerically and qualitatively, and untrustworthily, due to serial comparison of source data, received as binary code; taking of decision is possible about their mathematical nature and also transformation of source data in block 15, given in incorrect manner, to form, useable for parametric modeling procedure realization. |
 Device for parametric estimation of message streams distribution law / 2279125Device for parametric estimation of message streams distribution law contains: input amplifier, parameters computation block, average arithmetic values computation block, block for determining distribution type, distribution computing device, control block, intensiveness analysis block, block for analyzing trustworthiness of messages. Thus, it is possible to estimate parameters of distribution of homogeneous and heterogeneous streams of multi-packet messages with high trustworthiness, specific signs of pauses for which may be identified both quantitatively and qualitatively - untrustworthily, due to comparative analysis in block of bit series received in binary code from position of their match to signs of pauses and mathematically correct transformation, on basis of neuron networks theory, of untrustworthily identified signs of pauses to form, useable for performing procedure of parametric estimation of message streams distribution law. |
 Device for parametric estimation of partition law of message streams / 2281548Device for parametric estimation of message streams partition law contains input amplifier, parameters calculation block, block for calculation of average arithmetic values, block for determining type of partition, calculator of partition, control block, intensiveness analysis block, packet sign analysis block, block for transformation of type of packet sign, thus making it possible to estimate parameters of partition of homogeneous and non-homogeneous (mixed) streams of multi-packet messages with high trustworthiness, distinguishing marks of which packets (signs of beginning and end of information part of packets) may be identified both quantitatively and qualitatively - ambiguously, in uncertain manner, with utilization of linguistic variable, due to comparing analysis in block of incoming bit series for matching with signs of packets, appropriate for implemented exchange protocol and taking a decision about logic-mathematical nature of their identification attributes, which is mathematically correct, on basis of methods of theory of fuzzy sets, transformation in block of source data, characterizing signs of packets and identified in fuzzy form as type, useable for parametric estimation of message streams partition law. |
FIELD: computer science, possible use for determining random values distribution law and can be used for engineering of digital signals processing devices for classification of series of digital data on basis of available standard series.
SUBSTANCE: device has analog-digital converter, two memory block, n comparators, decoder, n counters.
EFFECT: simplified construction, maintenance and manufacture of device, increased speed of operation.
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The invention relates to computer science, designed to determine the distribution of the random variables and can be used in devices digital signal processing for classifying a sequence of digital data according to the available reference sequence.
It is known device [1], which contains an analog-to-digital Converter, an information input which is the input device, and a control input connected to the first output control unit, and the output of the combinational adder connected to the first information input of the memory block, the second information input connected to the output of the analog-to-digital Converter, the control input to the second output control unit, and the output of the memory block connected to the input of the combinational adder.
The disadvantages of this device are the complexity and poor performance since the implementation of the algorithm requires a large number of successive operations.
The closest to the technical nature of the claimed invention is selected as a prototype statistical analyzer [2], which contains an analog-to-digital Converter, the unit of comparison, registers, memory block, counter, additionally, the device includes a synchronizer, an adder, a demultiplexer, OR elements.
The disadvantages of the data devices are functional complexity and consequently poor performance.
The aim of the invention is the simplification of the device and improving its performance.
This objective is achieved in that in the known device containing an analog-to-digital Converter, the unit of comparison, the first block of memory, counters, ADC input is an input device according to the invention introduced the second memory block, n Comparators and the decoder, and the number of counters is increased and is equal to the number of Comparators, the first inputs of the Comparators connected to the output of the analog-to-digital Converter, the second inputs of Comparators connected to the output of the first memory block, the outputs of the Comparators are connected to the inputs of a decoder whose outputs are connected to inputs of counters, the outputs of the counters are connected to the inputs of the memory block.
The novelty of technical solutions is available in the claimed device of new circuit elements of the second memory block, n Comparators and decoder.
Thus, the invention conforms to the criterion "novelty".
Analysis of the known technical solutions in the study and related areas allows us to conclude that the introduced functional units known. However, their introduction into a device for classifying a sequence of digital signals with the above links gives it new properties. Introduced functional units interact thus, h is about, you can simplify the device and to improve its performance.
Thus, the invention meets the criterion of "Inventive step", as it is for the expert is not obvious from the prior art.
The invention can be used in digital systems disclaimerbuy and demuxing, in particular in digital satellite communication systems.
Thus, the invention meets the criterion of "Industrial applicability".
Figure 1 presents the structural electrical circuit of the device; figure 2 and 3 is a table explaining the operation of the device; figure 4 and 5 shows an example of construction of a conceptual model on the sample distributions; figure 6 shows how the code generation.
Device for classifying sequences (figure 1) contains an analog-to-digital Converter 1, the memory unit 2, the n Comparators 3, decoder 4, n counter 5, block 6 memory. The analog-digital Converter 1 is the input device, the first inputs of the comparator 3 is connected to the output of the analog-to-digital Converter 1, the second inputs of the comparator 3 is connected to the output of the memory unit 2. The outputs of the Comparators are connected to the inputs of the decoder 4, the outputs of which are connected with inputs of the counters 5. The outputs of the counter 5 is connected to the input unit 6 to the memory, the output of which is read found the probability in accordance with the table in figure 3.
The device DL is the classification of a sequence of digital signals (figure 1) works as follows. Prior to the input of the classified sequence in the memory unit 2 entered reference values related to the distribution law, compliance with which is determined. Analog sequence after digitizing the analog-to-digital Converter 1 is supplied to the first inputs of the Comparators 3, the second inputs of which consistently receives the reference values from the memory unit 2. When exceeding the analyzed values above the reference, the comparator produces a 1, otherwise 0. N number of Comparators and the number n of counters is determined by the length of the analyzed digital sequence. The outputs of the Comparators are connected to the inputs of the decoder 4, the conversion table shown in figure 2 (example 6 input values in the sequence).
Counters 5 sequentially calculate, for one step of processing a single value conversion decoder 4, which corresponds to the value of the original sequence. Accordingly, to process the entire sequence of n elements will take n steps to compute all the digits (counter values) of the output values, which after conversion to the memory block 6 determines the probability of assigning a sequence to a known class.
The outputs of the decoder are connected to the inputs of MF is tchikov 5, performing a bitwise calculation results of the evaluation sequence.
The outputs of the counters are connected to the inputs of unit 6 to the memory, the conversion table is shown in figure 3 (example 6 input values in the sequence).
Many practical tasks of detection, recognition, classification, identification in various fields of science and engineering can be reduced to the statistical testing of hypotheses. The most powerful criteria are based on statistics of the measures of the error density distributions determined as a function of the relationship of prawdopodobnie Kullback, χ-square, Pitman.
However, the practical application of these statistics is associated with the following difficulties:
- the lack of analytical models for the distributions of statistics in small samples;
the high computational cost required to compile statistics;
- the need to meet the requirements of the split variational number by the number of intervals (at least 8-10) and the number of elements in the intervals (at least 50-60), which is not always possible for small amounts of sample.
The assignment of the sequence to the known class is carried out by sequential comparison of the input values and the values corresponding to the known distribution and stored in the memory unit 2.
Theoretical fundamental is the legality of the conversion table, which is shown in figure 3, is a conceptual model of the canonical representation of pairs of distributions and statistical measures of the error density distributions using the model described in [3].
The conceptual model is an expression of the same law of distributionthrough another law
or the projection of the law
at the law
.
The graphic and the key conceptual model on the sample data shown in figure 4.
Expressions for calculating statistics measures the error on the Kullback (ΔI, ΔI*), Chi-square (Δχ2), Pitman (Δp) using the conceptual model have the form
where n1and n2- volumes of the first and second samples; Jν1=1 if ν1≠0 and Jν1=0 if νi=0; ν1- the number of elements of the second sample between (i-1)-th and i-th ordinal statistical variation of the number of the first sample.
If you define a sequence of values ν1that ν2, ..., ν6as the code for the specific conceptual model, for the above example (figure 4, 5) code is defined as 101231.
The method of forming the code shown in Fig.6, which shows the total variation range for the sample. On the X-axis by the symbol "x" denotes the element values of the first sample and the symbol "•" - value of the second sample.
Due to the additivity of the function statistician their values will be the same for all possible permutations. For example, the conceptual model codes 110231; 231110; 312110, etc. will have the same value statistics. Among the various conceptual models with the same value statistics is determined by the number of permutations in the code and is represented by the formula
The concept of numerical values of the code is defined as the number (n1+1) discharge and the basis of the positions of the n2i.e. as code, ordered by descending significant digits, starting with senior level.
Studies have shown the existence of a link between the values of the ordered code and statistics calculated for the conceptual model. The models with a larger numeric value codes correspond to large values of the statistic.
In the present work, the decision criteria instead of statistics defined by the formulas (1)to(4), it is suggested to use the corresponding numeric code values, which are the roads of decision making.
A necessary condition for the possibility of decision making is knowledge of the distribution statistics. Based on the foregoing, the proposed decision criterion, based on codes that allows you to opt out from the settlement of the above formulas(1)-(4).
Thus, a device for classifying a sequence of digital signals, performs the determination of the distribution law of random variables by sorting and matching them in the intervals of the reference sample, which excludes the operations of addition, multiplication, division, etc. and requires significantly less computational effort, thus increasing the operating speed of the device and simplifies it, excluding the computing units.
For the technical realization of the device for classifying a sequence of digital signals used by analog-to-digital Converter foreign production type AD9054ABST-200, a decoder, Comparators and counters implemented on the programmable logic integrated circuits XC2S50 memory storage schema structure XC17S50 - by XILINX, permanent storage device TS.
The present invention allows the determination of the distribution law of random variables to classify a sequence of digital data according to the available reference sequence.
The sources of information is AI
1. Auth. St. USSR № 830399, CL G 06 F 15/36, 1979.
2. Auth. St. USSR № 1310842, CL G 06 F 15/36, 1986.
3. L.N. Boris and Gleb. The decision criterion, based on codes in the tasks of detection and recognition. M, telecommunications, No. 7, 2001, S. 27-33.
Device for classifying a sequence of digital signals analog-to-digital Converter, a first memory unit for storing reference values of the corresponding distribution law, counters, analog-digital Converter is input device, characterized in that it introduced a second memory block for storing values of the probabilities according to the reference distribution, n Comparators and the decoder, and the number of counters is increased and is equal to the number of Comparators, the first inputs of the Comparators connected to the output of the analog-to-digital Converter, the second inputs of Comparators connected to the output of the first memory block, the outputs of the Comparators are connected to the inputs of the decoder, the outputs of which are connected with inputs of the counters, the outputs of the counters are connected to the inputs of the second memory block.