A fractional-N phase-locked loop (PLL) has a time-to-voltage converter with second order non linearity. The time-to voltage-converter provides an analog error signal indicating a phase difference between the reference clock signal with a period error and a feedback signal supplied by a fractional-N feedback divider. The spur results in quantization noise associated with the fractional-N feedback divider being frequency translated. To address the frequency translated noise, a spur cancellation circuit receives a residue signal indicative of the quantization noise and a spur signal indicative of the spur. The non-linearity of the time-to-voltage converter is mimicked digitally through terms of a polynomial generated to cancel the noise. The generated polynomial is coupled to a delta sigma modulator that controls a digital to analog converter that adds/subtracts a voltage value to/from the error signal to thereby cancel the quantization noise including the frequency translated quantization noise.

A data compression method and a data decompression method are provided. The method includes pruning an original data including a plurality of weight parameters, identifying at least one first weight parameter of which at least one first value is not changed by the pruning, among multiple weight parameters included in the pruned original data, and obtaining a first index data including location information of the at least one first weight parameter of which the at least one first value is not changed, identifying at least one second weight parameter of which at least one second value is changed by the pruning, among the multiple weight parameters included in the pruned original data, and substituting the at least one second weight parameter of which the at least one second value is changed with a don't care parameter.

A data compression method and a data decompression method are provided. The method includes pruning an original data including a plurality of weight parameters, identifying at least one first weight parameter of which at least one first value is not changed by the pruning, among multiple weight parameters included in the pruned original data, and obtaining a first index data including location information of the at least one first weight parameter of which the at least one first value is not changed, identifying at least one second weight parameter of which at least one second value is changed by the pruning, among the multiple weight parameters included in the pruned original data, and substituting the at least one second weight parameter of which the at least one second value is changed with a don't care parameter.