1. A clip for holding textiles in a folded position, the clip being formed of a flexible material that resists deformation, the clip comprising:
a single piece body comprising:
a connector extending across the clip; and
a pair of braces adjoining opposite ends of said connector, wherein said connector and said braces are integral portions of said single piece body.
2. A clip according to claim 1, wherein said clip is formed of a single continuous strip defining said connector and said braces.
3. A clip according to claim 2, wherein said single continuous strip comprises curved edges forming a hinge on either side of said connector, said hinge allowing said braces to move away from said connector to widen a gap formed between the braces and the connector.
4. A clip according to claim 1, wherein said single piece body defines holes for connecting a decorative element to the clip.
5. A clip according to claim 4, wherein said decorative element comprises buttons fitting into the holes defined by the single piece body.
6. A clip according to claim 1, wherein said single piece body defines holes for connecting a decorative accessory.
7. A clip according to claim 6, wherein said decorative accessory comprises buttons fitting into the holes defined by the single piece body.
8. A clip according to claim 1 wherein at least one of said braces is formed into the shape of the English letter S to form an S-shaped brace.
9. A clip according to claim 8, wherein a section of said S-shaped brace defines a grip for moving said brace away from said connector.
10. A clip according to claim 8, wherein said brace is so dimensioned such that a portion of said S-shaped brace allows for fitting a user’s finger therein to open said brace by moving said brace away from said connector.
11. A clip according to claim 1, wherein said single piece body is formed of a resilient material such that said braces move away from said connector to fit a folded fabric therein, and said braces move back to an original position upon removing said folded fabric.
12. A clip for retaining folded fabrics in a fixed position, the clip comprising:
a single piece body formed of a continuous strip, said single piece body comprising:
curved edges defining respective hinges on either end of said continuous strip; and
respective braces connected to said respective hinges, wherein said respective braces comprise curved portions for gripping said respective braces.
13. A clip for retaining folded fabrics according to claim 12, wherein said single piece body comprises a connector extending between said hinges, and said hinges are sufficiently resilient to allow for moving said braces away from said connector to allow for fitting a folded fabric between said braces and said connector.
14. A clip for retaining folded fabrics according to claim 12, wherein said braces comprise respective second curved portions fitting against a folded fabric held within the clip.
15. A clip for retaining folded fabrics according to claim 12, wherein said single piece body defines holes for attaching decorative elements or decorative accessories.
16. A clip comprising a connector having contoured ends that are sufficiently resilient to be moved away from said connector and fitting a folded fabric within the clip, said contoured ends compressing against said connector when said folded fabric is removed from said clip.
17. A clip according to claim 16, wherein said contoured ends are substantially shaped into the form of the English letter S.
18. A clip according to claim 16, wherein a first section of said contoured end is a grip for moving said contoured end away from said connector to fit a folded fabric within said clip.
19. A clip according to claim 16, wherein said connector defines holes for connecting decorative elements or decorative accessories to the clip.
20. A clip according to claim 16, wherein said contoured edges define holes for connecting decorative elements or decorative accessories to the clip.
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 for implementing an artificial neural network comprises:
connecting a plurality of receiving neurons to a plurality of transmitting neurons through memristive synapses, each memristive synapse having a weight;
initializing weights of the memristive synapses to a conductive state;
presenting a input vector through the memristive synapses to the plurality of receiving neurons; and
modifying the state of one or more of the memristive synapses based on the input vector.
2. The method according to claim 1, further comprising:
forcing all transmitting neurons to spike unconditionally, thereby sending a high electrical pulse through all memristive synapses connected to a receiving neuron; and
summing the signals received by the receiving neuron to produce a magnitude of the synapse weights.
3. The method according to claim 2, further comprising storing a representation of the magnitude of the synapse weights in a memristive device.
4. The method according to any of the above claims, in which the input vector is a complimentary coded binary input vector.
5. The method according to claim 4, further comprising determining a magnitude of a complimentary coded input vector, the magnitude of the complimentary coded input vector remaining constant for a given synaptic configuration.
6. The method according to claim 5, further comprising:
summing the signals received by a receiving neuron to produce an accumulated magnitude of the received signals;
calculating a match function by dividing the accumulated magnitude of the received signals by the magnitude of the complimentary coded input vector; and
calculating a choice function by dividing the accumulated magnitude of the received signals by the magnitude of the synapse weights.
7. The method according to claim 1, further comprising operating the artificial neural network within a synchronously timed architecture.
8. The method according to claim 7, further comprising:
calculating the magnitude of the synapse weights during a regulatory clock cycle;
calculating a winning neuron using a winner-take-all algorithm during an alternate clock cycle, in which the regulatory clock cycle and the alternative clock cycle are interleaved; and
modifying the state of the memristive synapses connected to the winning neuron by redistributing mobile dopants within the memristive synapses.
9. A method for implementing an artificial neural network comprises:
connecting a plurality of receiving neurons to a plurality of transmitting neurons through memristive synapses, each memristive synapse having a weight;
forcing all transmitting neurons to spike unconditionally, thereby sending a high electrical pulse through all memristive synapses connected to the plurality of receiving neurons; and
summing the signals received by the plurality of receiving neurons to produce a magnitude of the synapse weights for each of the plurality of receiving neurons.
10. The method according to claim 9, further comprising storing a representation of the magnitude of the synapse weights for each receiving neuron in a separate memristive device.
11. The method according to any of claim 9 or 10, further comprising
initializing weights of the memristive synapses to a conductive state;
presenting a binary input vector through the memristive synapses to the receiving neuron;
calculating a winning neuron using a winner-take-all algorithm; and
modifying the state of the memristive synapses connected to the winning neuron.
12. The method according to any of claim 9, 10 or 11, further comprising operating the artificial neural network within a synchronously timed architecture.
13. The method according to claim 12, further comprising:
calculating the magnitude of the synapse weights during a regulatory clock cycle; and
calculating a winning neuron during an alternate clock cycle, the regulatory clock cycle and the alternative clock cycle being interleaved.
14. The method according to claim 13, in which modifying the state of the memristive synapses connected to the winning neuron comprises increasing the electrical resistances of synapses between the winning neuron and transmitting neurons which did not transmit a signal during a current clock cycle.
15. A method for implementing an artificial neural network comprises:
connecting a receiving neuron to a plurality of transmitting neurons through memristive synapses;
determining a magnitude of a complimentary coded input vector;
initializing weights of the memristive synapses to a conductive state;
forcing all transmitting neurons to spike unconditionally, thereby sending a high electrical pulse through all memristive synapses connected to the receiving neuron;
summing the signals received by the receiving neuron to produce a magnitude of the synapse weights;
storing a representation of the magnitude of the synapse weights in a memristive device;
presenting a complimentary coded binary input vector through the memristive synapses to a receiving neuron;
summing the signals received by the receiving neuron to produce an accumulated magnitude of the received signals;
calculating a match function by dividing the accumulated magnitude of the received signals by magnitude of a complimentary coded input vector;
calculating a choice function by dividing the accumulated magnitude of the received signals by the magnitude of the synapse weights;
calculating a winning neuron using a winner-take-all algorithm; and
modifying the state of the memristive synapses connected to the winning neuron using a destructive interference of spikes between the plurality of transmitting neurons and the receiving neurons by decreasing the conductance of memristive synapses which are connected between the receiving neuron and non-spiking neurons.