Abstract: 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.

Abstract: Systems and methods for controlling frequency output of an electronic oscillator to compensate for effects of one or more parameters experienced by the oscillator incorporate artificial neural network processing functionality for generating correction signals. A neural network processing module includes one or more neurons which receive one or more inputs corresponding to parameters of an electronic oscillator, such as temperature and control voltage (or correction voltage). One or more sets of weights are calculated and applied to inputs to the neurons of the neural network as part of a training process, wherein the weights help shape the output of the neural network processing module. The neural network may include a linear summation module configured to provide an output signal that is at least partially based on outputs of the one or more neurons.

Abstract: 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.

Abstract: Systems and methods for controlling frequency output of an electronic oscillator to compensate for effects of one or more parameters experienced by the oscillator incorporate artificial neural network processing functionality for generating correction signals. A neural network processing module includes one or more neurons which receive one or more inputs corresponding to parameters of an electronic oscillator, such as temperature and control voltage (or correction voltage). One or more sets of weights are calculated and applied to inputs to the neurons of the neural network as part of a training process, wherein the weights help shape the output of the neural network processing module. The neural network may include a linear summation module configured to provide an output signal that is at least partially based on outputs of the one or more neurons.