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The signal was sampled at 32kHz and digitized to 12 bit precision.
Considering this requirement and constraint from logic size of FPGA, we adopt two types of filter, 8 delay taps filter with only 2 bit precision coefficient and 16 delay taps filter with 8 bit precision coefficient.
The latency of the architecture is n/2 clock cycles and throughput rate is one valid result per n/2 clocks for n bit precision.
The proposed compact genetic algorithm accelerates the conversion process up to 10.2× against the state of art methods reaching similar bit precision and robustness.
Once the data reaches the DAC, the waveform is output in 12 bit precision and run through a small op amp gain stage that introduces a DC offset to avoid clipping on the output.
However, the success of the reconstruction of this sparse signal is based on the assumption that the measurements have infinite bit precision.
Similar(51)
Thus, we need to increase the precision to 1.4-bit for low energy when the iteration count with 1-bit precision is repeatedly two or greater.
We set the result to be right adjusted so we have 10-bit precision.
Furthermore, the proposed architecture is coded for 16-bit precision using the VHDL language.
The proposed architecture is simple and offers 16-bit precision on input and output data.
The architecture is simple and offers 16-bit precision on input and output data.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com