Systems and methods of using an artificial neural network processing module to compensate a control voltage and create a linear output response for an electronic oscillator to produce a target frequency. The artificial neural network processing module includes one or more neurons which receive one or more inputs corresponding to the control voltage. The artificial neural network processing module is configured to provide a correction based at least in part on the control voltage and pre-calculated DAC values. The pre-calculated DAC values are determined in part by predetermined or predefined pull ranges and linear control voltage transfer functions. The artificial neural network processing module can preferably achieve a control voltage tuning linearity better than 0.5% linearity over an entire tuning range of ±−75 ppm.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A system for compensating the effects of control voltage on an electronic oscillator to achieve a target frequency output from the electronic oscillator, the system comprising: a neural network processing module operatively coupled to an input signal, the neural network processing module comprising a plurality of artificial neuron modules, wherein each of the plurality of artificial neuron modules is configured to receive the input signal and one or more pre-calculated DAC values and provide an output signal, for use in controlling the frequency output of the electronic oscillator, based at least in part on the input signal and the one of the one or more pre-calculated DAC values, wherein the one or more pre-calculated DAC values are derived at least in part from test data that corresponds to outputs generated by the electronic oscillator while experiencing a range of control voltage values. 2. The system of claim 1, wherein the input signal is related to a control voltage that corresponds to a value from the range of control voltage values. 3. The system of claim 2, further comprising a summation module configured to generate the input signal based on a summation of at least the control voltage and an output signal from a second neural network processing module, the second neural network processing module comprising a plurality of artificial neuron modules, wherein each of the plurality of neuron modules of the second neural network processing module receives one of one or more pre-calculated weights. 4. The system of claim 3, wherein the output signal from the second neural network processing module is a correction signal based at least in part on the one or more pre-calculated weights and an output signal from the electronic oscillator. 5. The system of claim 4, wherein the output signal from the electronic oscillator corresponds to a temperature of at least a portion of the electronic oscillator. 6. The system of claim 4, wherein the output signal from the electronic oscillator corresponds to an age of the electronic oscillator. 7. The system of claim 1, wherein the input signal corresponds to a temperature of at least a portion of the electronic oscillator. 8. The system of claim 2, wherein the neural network processing module is further configured to receive a second input signal, the second input signal relating to a temperature of at least a portion of the electronic oscillator. 9. The system of claim 1, further comprising a voltage conversion module, wherein the voltage conversion module is configured to convert the output signal from the neural network processing module into a correction voltage, and provide the correction voltage to the electronic oscillator. 10. The system of claim 1, further comprising a memory module, wherein the memory module is configured to store the one or more pre-calculated DAC values. 11. A system for providing a correction voltage to at least partially compensate for effects of parameters of an electronic device, the system comprising: a first neural network processing module comprising one or more processors and configured to receive a first input signal corresponding to a parameter of an electronic oscillator; and a second neural network processing module comprising one or more processors and configured to receive the first input signal and a second input signal corresponding in part to a control voltage and an output signal from the first neural network processing module; wherein each of the first and second neural network processing modules comprises a plurality of artificial neuron modules, wherein each of the plurality of artificial neuron modules receives one of one or more pre-calculated weights, wherein the first neural network processing module is configured to provide the output signal based at least in part on the first input signal and the one or more pre-calculated weights, and wherein the second neural network processing module is configured to provide a compensated control voltage based at least in part on the first and second input signals and the one or more pre-calculated DAC values. 12. The system of claim 11, wherein the one or more pre-calculated DAC values are derived at least in part from test data that corresponds to outputs generated by the electronic oscillator while experiencing a range of control voltage values, and wherein the control voltage of the second input signal corresponds to a value from the range of control voltage values. 13. The system of claim 11, wherein the one or more pre-calculated weights are derived at least in part from test data that corresponds to outputs generated by the electronic oscillator while experiencing a range of values of the parameter. 14. The system of claim 11, further comprising one or more voltage conversion modules configured to convert the output signal from the first neural network processing module into a correction signal. 15. The system of claim 14, further comprising a summation module configured to generate the second input signal based on the control voltage and the correction signal, and to provide the second input signal to the second neural network processing module. 16. The system of claim 11, wherein the first input signal corresponds to a temperature of at least a portion of the electronic oscillator. 17. The system of claim 11, further comprising a memory module, an analog-to-digital converter, a digital-to-analog converter, and a low-pass filter. 18. The system of claim 17, wherein the memory module is configured to store one or more values calculated by multiplying each of the one or more pre-calculated weights by a slope control variable, and store one or more values calculated by multiplying one or more bias inputs provided to the first neural network processing modules by the slope control variable. 19. A method of compensating for effects of control voltage on an electronic oscillator to achieve a target frequency output from the electronic oscillator, the method comprising: receiving test data from an electronic oscillator, the electronic oscillator being subject to a test control voltage, wherein the test data corresponds to outputs generated by the electronic oscillator while being subject to the test control voltage over a range of test control voltages; calculating a plurality of DAC values at least in part on the test data; providing a current control voltage to a neural network processing module including one or more processors; providing the plurality of DAC values to the neural network processing module; using the neural network processing module to calculate a neural network output signal based at least in part on the current control voltage and the plurality of DAC values; determining a correction voltage based at least in part on the neural network output signal; and providing the correction voltage to the electronic oscillator to at least partially control the frequency of the electronic oscillator. 20. The method of claim 19, wherein said calculating the first plurality of DAC values is performed prior to said receiving the current control voltage.