A method and system are provided for updating a neuron membrane potential in a spike time dependent plasticity model in a Neuromorphic system. The method includes approximating a shape of an analog spike signal from an axon input using a hardware-based digital axon timer. The method further includes generating a first intermediately updated neuron membrane potential value from a current axon timer value, a current synapse weight value and a current neuron membrane potential value using a first look-up table and an accumulator. The method also includes generating a second intermediately updated neuron membrane potential value with a leak decay effect using a second look-up table and the first intermediately updated neuron membrane potential value. The method additionally includes generating a final updated neuron membrane potential value based on a comparison of the second intermediately updated neuron membrane potential value with a neuron fire threshold level using a comparator.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for updating a neuron membrane potential in a spike time dependent plasticity model in a Neuromorphic system, the method comprising: approximating a shape of an analog spike signal from an axon input using a hardware-based digital axon timer; generating a first intermediately updated neuron membrane potential value from a current axon timer value, a current synapse weight value and a current neuron membrane potential value using a first look-up table and an accumulator; generating a second intermediately updated neuron membrane potential value with a leak decay effect using a second look-up table and the first intermediately updated neuron membrane potential value; and generating a final updated neuron membrane potential value based on a comparison of the second intermediately updated neuron membrane potential value with a neuron fire threshold level using a comparator. 2. The method of claim 1, further comprising computing an address for accessing the first look-up table as a product of the current synapse weight value and the current axon timer value. 3. The method of claim 2, wherein the product is used to access a corresponding neuron membrane potential delta value in the first look-up table. 4. The method of claim 1, wherein the first look-up table stores delta values for first intermediately updated neuron membrane potential values that are accumulated to generate the first intermediately updated neuron membrane potential value. 5. The method of claim 1, wherein the first intermediately updated neuron membrane potential value is used as an address to access the second look-up table for the leak decay effect. 6. The method of claim 1, wherein a selection of a first case or a second case is based on a result of the comparison, the first case corresponding to a neuron firing, the second case corresponding to a lack of the neuron firing, and wherein for the final updated neuron membrane potential value, a next or final updated neuron membrane potential value is reset to zero or a pre-determined preset value and a neuron fire spike is generated and output in the first case, or the second intermediately updated value is used as the final updated neuron membrane potential value without generating and outputting the neuron fire spike in the second case. 7. The method of claim 1, wherein the current synapse weight value is stored in a random access memory having a plurality of rows and a plurality of columns, the random access memory being configured to store a plurality of synapse weight values for a plurality of synapses occurring between a plurality of axons and a plurality of dendrites, wherein one of the plurality of memory rows corresponds to one of the plurality of axons and one of the plurality of memory columns corresponds to one of the plurality of dendrites. 8. The method of claim 1, wherein said approximating step comprises presetting the axon timer to a certain maximum value responsive to an input signal to a corresponding axon. 9. The method of claim 8, further comprising decrementing an axon timer value, starting at a certain maximum value over several evaluation cycles, to obtain an elapsed time since a last axon digital input spike for the corresponding axon. 10. The method of claim 1, wherein at least one of the first look-up table and the second look-up table are loaded with values obtained from measurements of actual neurons, simulation results or equations of approximation models. 11. The method of claim 1, wherein respective access frequencies of the first look-up table and the second look-up table are different for a same evaluation cycle. 12. A computer program product for updating a neuron membrane potential in a spike time dependent plasticity model in a Neuromorphic system, the computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to perform a method comprising: approximating a shape of an analog spike signal from an axon input using a hardware-based digital axon timer; generating a first intermediately updated neuron membrane potential value from a current axon timer value, a current synapse weight value and a current neuron membrane potential value using a first look-up table and an accumulator; generating a second intermediately updated neuron membrane potential value with a leak decay effect using a second look-up table and the first intermediately updated neuron membrane potential update; and generating a final updated neuron membrane potential value based on a comparison of the second intermediately updated neuron membrane potential value with neuron fire threshold level using a comparator. 13. The computer program product of claim 12, further comprising computing an address for accessing the first look-up table as a product of the current synapse weight value and the current axon timer value. 14. The computer program product of claim 13, wherein the product is used to access a corresponding neuron membrane potential delta value in the first look-up table. 15. The computer program product of claim 12, wherein the first look-up table stores delta values for first intermediately updated neuron membrane potential values that are accumulated to generate the first intermediately updated neuron potential value. 16. The computer program product of claim 12, wherein the first intermediately updated neuron membrane potential value is used as an address to access the second look-up table for the leak decay effect. 17. The computer program product of claim 12, wherein the current synapse weight value is stored in a random access memory having a plurality of rows and a plurality of columns, the random access memory being configured to store a plurality of synapse weight values for a plurality of synapses occurring between a plurality of axons and a plurality of dendrites, wherein one of the plurality of memory rows corresponds to one of the plurality of axons and one of the plurality of memory columns corresponds to one of the plurality of dendrites. 18. The computer program product of claim 12, wherein said approximating step comprises presetting the axon timer to a certain maximum value responsive to an input signal to a corresponding axon. 19. The computer program product of claim 18, further comprising decrementing an axon timer value, starting at a certain maximum value over several evaluation cycles, to obtain an elapsed time since a last axon digital input spike for the corresponding axon. 20. The computer program product of claim 12, wherein at least one of the first look-up table and the second look-up table are loaded with values obtained from measurements of actual neurons, simulation results or equations of approximation models. 21. The computer program product of claim 12, wherein respective access frequencies of the first look-up table and the second look-up table are different for a same evaluation cycle. 22. The computer program product of claim 12, wherein a selection of a first case or a second case is based on a result of the comparison, the first case corresponding to a neuron firing, the second case corresponding to a lack of the neuron firing, and wherein for the final updated neuron membrane potential value, a next or final updated neuron membrane potential value is reset to zero or a pre-determined preset value and a neuron fire spike is generated and output in the first case, or the second intermediately updated value is used as the final updated neuron membrane potential value without generating and outputting the neuron fire spike in the second case. 23. A system for updating a neuron potential in a spike time dependent plasticity model in a Neuromorphic system, the system comprising: a hardware-based digital axon timer for approximating an analog spike signal from an axon input; a processor configured to: generate a first intermediately updated neuron membrane potential value from a current axon timer value, a current synapse weight value and a current neuron membrane potential value using a first look-up table and accumulator; generate a second intermediately updated neuron membrane potential value with a leak decay effect using a second look-up table and the first intermediately updated neuron membrane potential value; and generate final updated neuron membrane potential value based on a comparison of the second intermediately updated neuron membrane potential value with a neuron fire threshold level using a comparator. 24. The system of claim 23, wherein the processor is further configured to compute an address for accessing the first look-up table as a product of the current synapse weight value and the current axon timer value. 25. The system of claim 23, wherein the first intermediately updated neuron membrane potential value is used as an address to access the second look-up table for the leak decay effect.