A method for configuring an artificial neuron includes receiving a set of input spike trains comprising asynchronous pulse modulation coding representations. The method also includes generating output spikes representing a similarity between the set of input spike trains and a spatial-temporal filter.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for configuring an artificial neuron, comprising: receiving a set of input spike trains comprising asynchronous pulse modulation coding representations; and generating output spikes representing a similarity between the set of input spike trains and a spatial-temporal filter. 2. The method of claim 1, in which the similarity comprises a continuous time squashed dot product or a radial basis function. 3. The method of claim 1, in which the input spike trains are sampled on an event-basis. 4. The method of claim 1, in which the artificial neuron comprises a Leaky-Integrate and Fire (LIF) neuron or a Spike Response Model (SRM) neuron. 5. The method of claim 1, in which the output spikes are unipolar, bipolar or multi-valued. 6. The method of claim 5, in which the bipolar output spikes are represented using Address Event Representation (AER) packets. 7. An apparatus for configuring an artificial neuron, comprising: a memory; and at least one processor coupled to the memory, the at least one processor being configured: to receive a set of input spike trains comprising asynchronous pulse modulation coding representations; and to generate output spikes representing a similarity between the set of input spike trains and a spatial-temporal filter. 8. The apparatus of claim 7, in which the similarity comprises a continuous time squashed dot product or a radial basis function. 9. The apparatus of claim 7, in which the at least one processor is further configured to sample the input spike trains on an event-basis. 10. The apparatus of claim 7, in which the artificial neuron comprises a Leaky-Integrate and Fire (LIF) neuron or a Spike Response Model (SRM) neuron. 11. The apparatus of claim 7, in which the at least one processor is further configured to generate output spikes that are unipolar, bipolar or multi-valued. 12. The apparatus of claim 11, in which the bipolar output spikes are represented using Address Event Representation (AER) packets. 13. An apparatus for configuring an artificial neuron, comprising: means for receiving a set of input spike trains comprising asynchronous pulse modulation coding representations; and means for generating output spikes representing a similarity between the set of input spike trains and a spatial-temporal filter. 14. The apparatus of claim 13, in which the similarity comprises a continuous time squashed dot product or a radial basis function. 15. The apparatus of claim 13, in which the input spike trains are sampled on an event-basis. 16. The apparatus of claim 13, in which the artificial neuron comprises a Leaky-Integrate and Fire (LIF) neuron or a Spike Response Model (SRM) neuron. 17. The apparatus of claim 13, in which the output spikes are unipolar, bipolar or multi-valued. 18. The apparatus of claim 17, in which the bipolar output spikes are represented using Address Event Representation (AER) packets. 19. A computer program product for configuring an artificial neuron, comprising: a non-transitory computer readable medium having encoded thereon program code, the program code comprising: program code to receive a set of input spike trains comprising asynchronous pulse modulation coding representations; and program code to generate output spikes representing a similarity between the set of input spike trains and a spatial-temporal filter. 20. The computer program product of claim 19, in which the similarity comprises a continuous time squashed dot product or a radial basis function. 21. The computer program product of claim 19, further comprising program code to sample the input spike trains on an event-basis. 22. The computer program product of claim 19, in which the artificial neuron comprises a Leaky-Integrate and Fire (LIF) neuron or a Spike Response Model (SRM) neuron. 23. The computer program product of claim 19, further comprising program code to generate output spikes that are unipolar, bipolar or multi-valued. 24. The computer program product of claim 23, in which the bipolar output spikes are represented using Address Event Representation (AER) packets.