Musical instrument pickup signal processor

1. A system comprising:

an interface configured to receive information from one or more sensors associated with a first instrument;

a processing module configured to generate a processed signal by processing the received information according to a predetermined computational model, wherein parameters of the computational model are predetermined by operating on one or more stored sound recordings;

a parameter module configured to determine parameters for the computational model that, when applied to a first stored recording, minimize the difference between the first stored recording and a second stored recording, the first stored recording being received from one or more sensors associated with a second instrument, and the second stored recording being received from one or more microphones; and

an output interface configured to output the processed signal.

2. The system of claim 1 , wherein the information received from the one or more sensors is an analog signal that is converted to a digital signal prior to reaching the processing module.

3. The system of claim 1 , wherein the processed signal is a digital signal, and is converted into an analog signal before being output.

4. The system of claim 1 , wherein the first stored recording and the second stored recording are associated with the same musical instrument.

5. The system of claim 1 , wherein the computational model comprises a learning model.

6. The system of claim 5 , wherein the difference between the first stored recording and the second stored recording is the mean square error.

7. The system of claim 5 , wherein the difference between the first stored recording and the second stored recording is computed in the frequency domain.

8. The system of claim 5 , wherein the computational model comprises a plurality of sub-models, the parameters of each sub-model being determined by operating on pre-determined portions of one or more stored sound recordings, wherein the predetermined portions of the stored sound recordings are statistically similar.

9. The system of claim 1 , wherein the one or more sensors associated with the second instrument comprise one or more musical instrument pickups.

10. The system of claim 1 , wherein the first instrument and the second instrument comprise the same instrument.

11. A method comprising:

receiving, an electronic communication from one or more sensors;

performing numerical operations on the electronic communication;

wherein the numerical operations are determined by a predetermined computational model;

wherein the parameters of the computational model are predetermined by operating on stored sound recordings;

wherein predetermining the parameters of the computational model comprises:

assigning a stored recording made using a pickup attached to an instrument as the input to the computational model;

assigning a stored recording made using one or more external microphones of a musical instrument as the output of the computational model;

determining parameters for the computational model that, when applied to the input, minimize the variation between the model input and output; and

outputting the operated on electronic communication.

12. The method of claim 11 , wherein the electronic communication from the one or more sensors is an analog signal that is converted into a digital signal prior to performing numerical operations and the output electronic communication is a digital signal that is converted into an analog signal after being output.

13. The method of claim 11 , wherein the stored recording made using a pickup and the stored recording made using one or more microphones are made with the same musical instrument.

14. The method of claim 11 , wherein the variation between the model input and output is the mean square error.

15. The method of claim 11 , wherein the computational model comprises a plurality of sub-models, the parameters of each sub-model being determined by operating on pre-determined portions of one or more stored sound recordings.

16. One or more non-transitory computer readable media having instructions operable to cause one or more processors to perform the operations comprising:

receiving, an electronic communication from one or more sensors;

generating a processed signal by performing numerical operations on the electronic communication;

wherein the numerical operations are determined by a computational model;

wherein the parameters of the computational model are determined by processing one or more stored sound recordings;

wherein determining the parameters of the computational model comprises:

assigning a first stored recording as the input to the computational model, the first stored recording being made using a pickup attached to an instrument;

assigning a second stored recording as the output of the computational model, the second stored recording being made using one or more external microphones of a musical instrument; and

determining parameters for the computational model that, when applied to the first stored recording, minimize the difference between the first stored recording and the second stored recording; and

outputting the processed signal.

17. The one or more non-transitory computer readable media of claim 16 , wherein the electronic communication from the one or more sensors is an analog signal that is converted into a digital signal prior to performing numerical operations and the processed signal is a digital signal that is converted into an analog signal after being output.

18. The one or more non-transitory computer readable media of claim 16 , wherein the first stored recording and the second stored recording are made with the same musical instrument.

19. The one or more non-transitory computer readable media of claim 16 , wherein the difference between the first stored recording and the second stored recording is the mean square error.

20. The one or more non-transitory computer readable media of claim 16 , wherein the difference between the first stored recording and the second stored recording is computed in the frequency domain.