Neural comprising means for calculating a norm or a distance
First Claim
1. A neural processor, comprising neural calculation means for extracting a root Q of a quantity X, which root constitutes either a norm of data or a distance between data, the neural calculation means comprising:
- at least one first neuron for recursively calculating a series of contributions Δ
Qi =qi ·
Bi which together form an expression of the root Q on an arbitrary base;
at least one second neuron, fed by said at least one first neuron, for recursively updating a partial root QP by accumulating said contributions Δ
Qi in order to deliver the root Qwhere i is an integer index and qi is an integer coefficient of the ith power of base B.
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Abstract
A neural processor, comprising neural calculation apparatus (30, NQ, RQ) which extracts a root Q of a quantity X, said root constituting either a norm of a data or a distance between data. The calculation apparatus calculates (30) by iteration a series of contributions ΔQi which are used (NQ, RQ) to update a partial root QP which becomes the root Q at the end of calculation. The calculation can be performed on an arbitrary arithmetic base which determines the number of neurons utilized and also the accuracy of calculation. It is possible to execute the calculation of a partial remainder (NR, RR). Several programming modes are presented.
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Citations
15 Claims
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1. A neural processor, comprising neural calculation means for extracting a root Q of a quantity X, which root constitutes either a norm of data or a distance between data, the neural calculation means comprising:
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at least one first neuron for recursively calculating a series of contributions Δ
Qi =qi ·
Bi which together form an expression of the root Q on an arbitrary base;at least one second neuron, fed by said at least one first neuron, for recursively updating a partial root QP by accumulating said contributions Δ
Qi in order to deliver the root Qwhere i is an integer index and qi is an integer coefficient of the ith power of base B. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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8. A processor as claimed in claim 6,
wherein for B=2, the at least one first neuron executes the calculating and first and second determining operations and the at least one second neuron (NQ) executes the updating of the partial root; - and
further comprising a third neuron (NR) for executing the updating of the partial remainder.
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9. A processor as claimed in claim 1, wherein the calculation means are further for calculating a square root by calculating a partial remainder RPi, by performing the following additional operations:
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setting the partial remainder initially to the quantity X, updating the partial remainder by iteration so that one of the following equations holds;
space="preserve" listing-type="equation">RP.sub.i =RP.sub.i+1 -Δ
Q.sub.i ·
(2·
QP.sub.i+1 +Δ
Q.sub.i) or
space="preserve" listing-type="equation">RP.sub.i =RP.sub.i+1 -Δ
Q.sub.i (2·
QP.sub.i -Δ
Q.sub.i)where i is an integer index which is initialized to a maximum value and decremented to a predetermined minimum value which yields a desired precision for Q; and d is an integer representing the degree of the root Q.
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- 10. A processor as claimed in claim 9, wherein the calculation means are further for calculating a plurality of quantities SDj according to the following equation
- space="preserve" listing-type="equation">SD.sub.j =RP.sub.i +1-j·
B.sup.i ·
(2·
QP.sub.i+1 +j·
B.sup.i)
where j is an integer index varying from 1 to B-1. - space="preserve" listing-type="equation">SD.sub.j =RP.sub.i +1-j·
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11. A processor as claimed in claim 1, wherein the processor performs a root calculation at one instant and performs neural resolving and/or learning tasks at another instant.
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12. A processor as claimed in claim 1, wherein the processor receives components of a vector and calculates said quantity X to be equal to the sum of powers of degree d of each of said components.
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13. A processor as claimed in claim 1, wherein the processor receives vector components and calculates said quantity X, for vectors taken two by two, so that X is equal to the sum of the powers of degree d of the differences between said components of the same order.
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14. A neural processor for extracting a root Q of a quantity X, which root constitutes either a norm of a data or a distance between data, the processor comprising a first neuron (NA) for
calculating a plurality of quantities SDj according to the following equation: -
space="preserve" listing-type="equation">SD.sub.j =X--(QP.sub.i+1 +j·
B.sup.i).sup.dsaid plurality of quantities resulting from B-1 operations performed by at least one neuron for an index j varying from 1 to B-1, i being an integer index initially equal to a predetermined maximum; first determining a value j=qi for which;
space="preserve" listing-type="equation">sgn(SD.sub.j)≠
sgn(SD.sub.j+1)where SD0 ≧
0, SDB <
0, sgn(0)=+1, B is 2, and d is the degree of the root; and
a second neuron (NQ) forsecond determining a contribution Δ
Qi =qi ·
Bi ;third determining a new partial root such that;
space="preserve" listing-type="equation">QP.sub.i =Qpi+1+Δ
Qi.15. - View Dependent Claims (15)
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Specification