A method and system are provided for updating synapse weight values in neuromorphic system with Spike Time Dependent Plasticity model. The method includes selectively performing, by a hardware-based synapse weight incrementer or decrementer, one of a synapse weight increment function or decrement function, each using a respective lookup table, to generate updated synapse weight values responsive to spike timing data. The method further includes storing the updated synapse weight values in a memory. The method additionally includes performing, by a hardware-based processor, a learning process to integrate the updated synapse weight values stored in the memory into the Spike Time Dependent Plasticity model neuromorphic system for improved neuromorphic simulation.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for updating synapse weight values in a Spike Time Dependent Plasticity model neuromorphic system, comprising: selectively performing, by a hardware-based synapse weight incrementer or decrementer, one of a synapse weight increment function or decrement function, each using a respective lookup table, to generate updated synapse weight values responsive to spike timing data; storing the updated synapse weight values in a memory; and performing, by a hardware-based processor, a learning process to integrate the updated synapse weight values stored in the memory into the Spike Time Dependent Plasticity model neuromorphic system for improved neuromorphic simulation. 2. The method of claim 1, wherein contents of the respective lookup tables are based on contents of a simulation, or a hardware measurement, of synapse models. 3. The method of claim 2, further comprising, if there is missing data in the simulation or hardware measurement, calculating the missing data by at least one of interpolation and extrapolation, each using existing data. 4. The method of claim 1, further comprising supplying contents of the respective lookup tables based on a Spike Time Dependent Plasticity theory. 5. The method of claim 1, further comprising preloading contents of the respective lookup tables into the respective lookup tables. 6. The method of claim 1, further comprising supplying delta values of one of the synapse weight increment function and the synapse weight decrement function as contents of the respective lookup tables. 7. The method of claim 1, further comprising determining increment amounts of the synapse weight values using current synapse weight values and current Axon Timer values when at least one dendrite output (neuron fire) spike arises. 8. The method of claim 1, further comprising determining decrement amounts of the synapse weight values using current synapse weight values and current Dendrite Timer values when at least one axon input spike arises. 9. The method of claim 1, further comprising selecting, by a multiplexer, a result from one of the hardware-based synapse weight incrementer or the hardware-based synapse weight decrementer and saving the result in the memory. 10. A computer-readable storage medium including a computer-readable program, wherein the computer-readable program when executed on a computer causes the computer to perform the steps of: updating synapse weight values in a Spike Time Dependent Plasticity model neuromorphic system; selectively performing, by a hardware-based synapse weight incrementer or decrementer, one of a synapse weight increment function or decrement function, each using a respective lookup table, to generate updated synapse weight values responsive to spike timing data; storing the updated synapse weight values in a memory; and performing, by a hardware-based processor, a learning process to integrate the updated synapse weight values stored in the memory into the Spike Time Dependent Plasticity model neuromorphic system for improved neuromorphic simulation. 11. The computer readable storage medium of claim 10, wherein the computer-readable program when executed on the computer causes the computer to further perform the step of preparing, by the hardware-based processor, contents of the respective lookup tables, wherein the contents are based on at least one of: contents of a simulation; a hardware measurement of synapse models; and some equations to approximate the model performance. 12. A system for updating synapse weight values in a Spike Time Dependent Plasticity model neuromorphic system, comprising: at least one of a hardware-based synapse weight incrementer and a hardware-based synapse weight decrementer, each respectively configured to perform either a synapse weight increment function or a synapse weight decrement function, using a respective lookup table, to generate updated synapse weight values in response to spike timing data; a memory configured to store the updated synapse weight values; and a hardware-based processor configured to perform a learning process to integrate the updated synapse weight values stored in the memory into the Spike Time Dependent Plasticity model neuromorphic system for improved neuromorphic simulation. 13. The system of claim 12, wherein the hardware-based processor is further configured to prepare contents of the respective lookup tables, wherein the contents are based on at least one of: contents of a simulation; a hardware measurement of synapse models; and some equations to approximate the model performance. 14. The system of claim 13, wherein, if there is any missing data in the simulation or hardware measurement, the hardware-based processor is further configured to calculate the missing data by at least one of interpolation and extrapolation, each using existing data. 15. The system of claim 13, wherein the hardware-based processor is further configured to supply the contents of the respective lookup tables based on a Spike Time Dependent Plasticity theory. 16. The system of claim 13, wherein the hardware-based processor is further configured to preload the contents of the respective lookup tables into the respective lookup tables. 17. The system of claim 13, wherein the hardware-based processor is further configured to supply delta values of the synapse weight increment function and the synapse weight decrement function as the contents of the respective lookup tables. 18. The system of claim 12, wherein the hardware-based processor is further configured to determine increment amounts of the synapse weight values using current synapse weight values and current Axon Timer values when at least one dendrite output (neuron fire) spikes arise. 19. The system of claim 12, wherein the hardware-based processor is further configured to determine decrement amounts of the synapse weight values using current synapse weight values and current Dendrite Timer values when at least one axon input spikes arise. 20. The system of claim 12, further comprising a multiplexer configured to select a result from one of the hardware-based synapse weight incrementer or the hardware-based synapse weight decrementer and save the result in the memory.