1.-11. (canceled)
12. A regulator device for compensating for dispersions of a plurality of piezo actuated injectors in each case are assigned to cylinders of an internal combustion engine, comprising:
a control device configured to provide a cylinder-specific controlled variable and a command variable, of which a primary manipulated variable is a variable that represents an electrical power supplied during an activation cycle to the piezo actuator; and
a manipulated variable splitting unit where the input variable is a regulator value of the primary manipulated variable determined by the regulator is embodied for determining a total value of the primary manipulated variable as a function of the regulator value, for splitting the total value into a primary value of the primary manipulated variable and a secondary value of a secondary manipulated variable as a function of a lower andor upper threshold value of the total value where the manipulated variable splitting unit increases the secondary value beyond the amount needed for implementing the difference between the total value and the primary value if the regulator value exceeds the upper threshold value, and retaining the increase until the regulator value falls below a hysteresis threshold value in relation to the upper threshold value.
13. The regulator device as claimed in claim 12, wherein the manipulated variable splitting unit increasingly raises the secondary value beyond the amount needed to implement the difference between the regulator value and the primary value until the regulator value falls below a regulation reserve threshold value in relation to the upper threshold value.
14. A regulator device for compensating for dispersions of a plurality of piezo actuated injectors in each case are assigned to cylinders of an internal combustion engine that supplies a cylinder-specific controlled variable and a command variable to a regulator, of which the primary manipulated variable is a variable which represents an electrical power supplied during an activation cycle to the piezo actuator, comprising:
a manipulated variable splitting unit wherein the input variable is a regulator value of the primary manipulated variable determined by the regulator and which is embodied for determining a total value of the primary manipulated variable as a function of the regulator value, for splitting the total value into a primary value of the primary manipulated variable and a secondary value of a secondary manipulated variable as a function of a lower andor upper threshold value of the total value, with the manipulated variable splitting unit being embodied to increase the secondary value beyond the amount needed for implementing the difference between the total value and the primary value, if the regulator value falls below the lower threshold value, and retaining the decrease until the regulator value exceeds a hysteresis threshold value in relation to the lower threshold value.
15. The regulator device as claimed in claim 14, wherein the manipulated variable splitting unit increasingly reduces the secondary value beyond the amount needed for the implementation of the difference of the regulator value and the primary value until the regulator value exceeds a regulator reserve threshold value in relation to the lower threshold value.
16. The regulator device as claimed in claim 15, wherein the manipulated variable splitting unit increases the secondary value beyond the amount needed to implement the difference between the total value) and of the primary value, if the regulator value exceeds the upper threshold value, and to retain the increase until the regulator value falls below a hysteresis threshold value in relation to the upper threshold value.
17. The regulator device as claimed in claim 16, wherein the manipulated variable splitting unit raises the secondary value beyond the amount needed to implement the difference between the regulator value and the primary value until the regulator value falls below a regulation reserve threshold value in relation to the upper threshold value.
18. The regulator device as claimed in claim 17, wherein the manipulated variable splitting unit limits the range of values of the primary value in respect of its lower value range limit to the lower threshold value, andor in relation to its upper value range limit, to the upper threshold value.
19. The regulator device as claimed in claim 18, wherein the regulator is a cylinder-specific Lambda regulator.
20. The regulator device as claimed in claim 19, wherein the regulator is an uneven running regulator.
21. The regulator device as claimed in claim 20, wherein the regulator determines the total value as a function of a pilot control value of the primary manipulated variable, which is determined as a function of at least one operating variable of the internal combustion engine.
22. The regulator device as claimed in claim 21, wherein the secondary manipulated variable represents the injection time of the injector.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A method of computing an estimation of maximum total sales over streaming items, comprising:
receiving items with associated item values as bids on the items received;
individually designating each item having an associated value as an item value pair;
establishing value ranges to place item value pairs, wherein the value ranges are distinct and the value ranges are respectively designated from a first value range through a last value range, where the first value range is a lowest value range, the last value range is a highest value range, and other value ranges are in between the first value range and the last value range;
performing an iteration comprising:
respectively adding each of the item value pairs into the value ranges according to each of the associated values for the item value pairs;
removing repeated item value pairs associated with a same item that are in same ones of the value ranges;
randomly selecting a number of the item value pairs to remove from each of the value ranges, the number based on an error factor;
computing an estimate of a total maximum value of the bids for the item value pairs in all of the value ranges based on summation of all the value ranges and a scale factor.
2. The method of claim 1, wherein the iteration further comprises determining when identical items are in different ones of the value ranges;
removing the identical items from lower ones of the value ranges, which results in the items, corresponding to the item value pairs, only being in a highest possible value range for the associated values and results in duplicative items not being in any of the value ranges.
3. The method of claim 2, further comprising repeatedly performing the iteration a predetermined number of times to generate a first estimate of the total maximum value through a last estimate of the total maximum value; and
arranging the first estimate of the total maximum value through the last estimate of the total maximum value in order according to numerical values.
4. The method of claim 3, further comprising selecting a median of the numerical values arranged in order as the estimate of the total maximum value of the bids for the total sales.
5. The method of claim 1, wherein respectively adding each of the item value pairs into the value ranges according to each of the associated values for the item value pairs comprises a first phase which includes:
applying a hash function to each particular item in a particular value range to obtain a random hash function number, the particular item has a particular item value pair;
determining when the random hash function number is greater than a threshold, the threshold is a function of a total number of the items;
when the random hash function number is greater than the threshold, not adding the particular item value pair to the particular value range which results in the particular item value pair being randomly discarded;
when the random hash function number is less than the threshold, adding the particular item value pair to the particular value range; and
respectively repeating the first phase for all of the value ranges.
6. The method of claim 5, wherein the first phase further comprises:
determining that the number of the item value pairs in the particular value range is greater than a bound size, the bound size is a function of the error factor; and
when the number of the item value pairs in the particular value range is greater than the bound size, applying a second phase.
7. The method of claim 6, wherein reducing the number of the item value pairs in each of the value ranges respectively based on the error factor, by randomly selecting the item value pairs to remove from each of the value ranges comprises the second phase which includes:
decreasing the threshold by a predetermined amount;
applying the hash function to the particular item in the particular value range to obtain the random hash function number;
determining that the random hash function number is greater than the threshold decreased by the predetermined amount;
when the random hash function number is greater than the threshold decreased by the predetermined amount, removing the particular item value pair for the particular item from the particular value range; and
respectively repeating the second phase for all of the items in the particular value range resulting in the number of the item value pairs in the particular value range being reduced by randomly removing the item value pairs.
8. The method of claim 1, wherein computing the estimate of the total maximum value of the bids for the item value pairs in all of the value ranges based on the scale factor comprises:
adding the associated values of all the bids in the value ranges for the items to obtain a sum; and
multiplying the sum by the scale factor corresponding to the number of the item value pairs in each of the value ranges that were randomly removed, the scale factor increasing the sum to account for the number of the item value pairs randomly removed.
9. A computer program product for computing an estimation of maximum total sales over streaming items, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code executable by a computer to:
receive items with associated item values as bids on the items received;
individually designate each item having an associated value as an item value pair;
establish value ranges to place item value pairs, wherein the value ranges are distinct and the value ranges are respectively designated from a first value range through a last value range, where the first value range is a lowest value range, the last value range is a highest value range, and other value ranges are in between the first value range and the last value range; and
perform an iteration comprising:
respectively adding each of the item value pairs into the value ranges according to each of the associated values for the item value pairs;
removing repeated item value pairs that are in same ones of the value ranges;
randomly selecting a number of the item value pairs to remove from each of the value ranges, the number based on an error factor;
computing an estimate of a total maximum value of the bids for the item value pairs in all of the value ranges based on summation of all the value ranges and a scale factor.
10. The computer program product of claim 9, wherein the iteration further comprises determining when identical items are in different ones of the value ranges;
removing the identical items from lower ones of the value ranges, which results in the items, corresponding to the item value pairs, only being in a highest possible value range for the associated values and results in duplicative items not being in any of the value ranges.
11. The computer program product of claim 10, further comprising repeatedly performing the iteration a predetermined number of times to generate a first estimate of the total maximum value through a last estimate of the total maximum value; and
arranging the first estimate of the total maximum value through the last estimate of the total maximum value in order according to numerical values.
12. The computer program product of claim 11, further comprising selecting a median of the numerical values arranged in order as the estimate of the total maximum value of the bids for the total sales.
13. The computer program product of claim 9, wherein respectively adding each of the item value pairs into the value ranges according to each of the associated values for the item value pairs comprises a first phase which includes:
applying a hash function to each particular item in a particular value range to obtain a random hash function number, the particular item has a particular item value pair;
determining when the random hash function number is greater than a threshold, the threshold is a function of a total number of the items;
when the random hash function number is greater than the threshold, not adding the particular item value pair to the particular value range which results in the particular item value pair being randomly discarded;
when the random hash function number is less than the threshold, adding the particular item value pair to the particular value range; and
respectively repeating the first phase for all of the value ranges.
14. The computer program product of claim 13, wherein the first phase further comprises:
determining that the number of the item value pairs in the particular value range is greater than a bound size, the bound size is a function of the error factor; and
when the number of the item value pairs in the particular value range is greater than the bound size, applying a second phase.
15. The computer program product of claim 14, wherein reducing the number of the item value pairs in each of the value ranges respectively based on the error factor, by randomly selecting the item value pairs to remove from each of the value ranges comprises the second phase which includes:
decreasing the threshold by a predetermined amount;
applying the hash function to the particular item in the particular value range to obtain the random hash function number;
determining that the random hash function number is greater than the threshold decreased by the predetermined amount;
when the random hash function number is greater than the threshold decreased by the predetermined amount, removing the particular item value pair for the particular item from the particular value range; and
respectively repeating the second phase for all of the items in the particular value range resulting in the number of the item value pairs in the particular value range being reduced by randomly removing the item value pairs.
16. The computer program product of claim 9, wherein computing the estimate of the total maximum value of the bids for the item value pairs in all of the value ranges based on the scale factor comprises:
adding the associated values of all the bids in the value ranges for the items to obtain a sum; and
multiplying the sum by the scale factor corresponding to the number of the item value pairs in each of the value ranges that were randomly removed, the scale factor increasing the sum to account for the number of the item value pairs randomly removed.
17-20. (canceled)