A method for providing diversity in a set of neurons in a neuron model includes retrieving a set of parameters for the set of neurons. The method also includes perturbing the set of parameters based on a neuron identification value, a level of perturbation for each parameter and/or parameter values.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for providing diversity in a set of neurons in a neuron model comprising: retrieving a set of parameters for the set of neurons; and perturbing the set of parameters based at least in part on a neuron identification value, a level of perturbation for each parameter and/or parameter values. 2. The method of claim 1, in which the perturbing is based at least in part on a percentage range of perturbation around a mean value of at least one parameter value. 3. The method of claim 1, in which the perturbing includes dithering at least a significant bit of a parameter value for at least a portion of the set of neurons. 4. The method of claim 1, in which the level of perturbation of the set of parameters is based at least in part on network behavior and input statistics. 5. The method of claim 1, in which the level of perturbation of the set of parameters is based at least in part on desired output. 6. The method of claim 1, in which the perturbing is based at least in part on a desired probability distribution. 7. The method of claim 1, in which the level of perturbation of the set of parameters is based at least in part on a level of diversity in spike times. 8. The method of claim 1, in which the level of perturbation of the set of parameters is based at least in part on a level of diversity in synaptic weights. 9. An apparatus for providing diversity in a set of neurons in a neuron model comprising: a memory; and at least one processor coupled to the memory, the at least one processor being configured: to retrieve a set of parameters for the set of neurons; and to perturb the set of parameters based at least in part on a neuron identification value, a level of perturbation for each parameter and/or parameter values. 10. The apparatus of claim 9, in which the at least one processor is further configured to perturb the set of parameters based at least in part on a percentage range of perturbation around a mean value of at least one parameter value. 11. The apparatus of claim 9, in which the at least one processor is further configured to dither at least a significant bit of a parameter value for at least a portion of the set of neurons. 12. The apparatus of claim 9, in which the level of perturbation of the set of parameters is based at least in part on network behavior and input statistics. 13. The apparatus of claim 9, in which the level of perturbation of the set of parameters is based at least in part on desired output. 14. The apparatus of claim 9, in which the at least one processor is further configured to perturb the set of parameters based at least in part on a desired probability distribution. 15. The apparatus of claim 9, in which the level of perturbation of the set of parameters is based at least in part on a level of diversity in spike times. 16. The apparatus of claim 9, in which the level of perturbation of the set of parameters is based at least in part on a level of diversity in synaptic weights. 17. An apparatus for providing diversity in a set of neurons in a neuron model comprising: means for retrieving a set of parameters for the set of neurons; and means for perturbing the set of parameters based at least in part on a neuron identification value, a level of perturbation for each parameter and/or parameter values. 18. The apparatus of claim 17, in which the means for perturbing perturbs the set of parameters based at least in part on a percentage range of perturbation around a mean value of at least one parameter value. 19. The apparatus of claim 17, in which the means for perturbing dithers at least a significant bit of a parameter value for at least a portion of the set of neurons. 20. The apparatus of claim 17, in which the level of perturbation of the set of parameters is based at least in part on network behavior and input statistics. 21. The apparatus of claim 17, in which the level of perturbation of the set of parameters is based at least in part on desired output. 22. The apparatus of claim 17, in which the means for perturbing perturbs the set of parameters based at least in part on a desired probability distribution. 23. The apparatus of claim 17, in which the level of perturbation of the set of parameters is based at least in part on a level of diversity in spike times. 24. The apparatus of claim 17, in which the level of perturbation of the set of parameters is based at least in part on a level of diversity in synaptic weights. 25. A computer program product for providing diversity in a set of neurons in a neuron model comprising: a non-transitory computer readable medium having encoded thereon program code, the program code comprising: program code to retrieve a set of parameters for the set of neurons; and program code to perturb the set of parameters based at least in part on a neuron identification value, a level of perturbation for each parameter and/or parameter values. 26. The computer program product of claim 25, further comprising program code to perturb the set of parameters based at least in part on a percentage range of perturbation around a mean value of at least one parameter value. 27. The computer program product of claim 25, further comprising program code to dither at least a significant bit of a parameter value for at least a portion of the set of neurons. 28. The computer program product of claim 25, in which the level of perturbation of the set of parameters is based at least in part on network behavior and input statistics. 29. The computer program product of claim 25, in which the level of perturbation of the set of parameters is based at least in part on desired output. 30. The computer program product of claim 25, further comprising program code to perturb the set of parameters based at least in part on a desired probability distribution. 31. The computer program product of claim 25, in which the level of perturbation of the set of parameters is based at least in part on a level of diversity in spike times. 32. The computer program product of claim 25, in which the level of perturbation of the set of parameters is based at least in part on a level of diversity in synaptic weights.