Data Acquisition from Real World Objects based on Nonuniform Signal Sampling and Processing
Kaspars Sudars · 2012
The paper summarizes obtained research and practical results reported in the author’s doctoral Thesis “Data Acquisition from Real World Objects”. Work is focused on methods and algorithms for data acquisition from real world objects, and it is based on the theory of non-traditional Digital Signal Processing, including non-uniform sampling and pseudo-randomized quantizing. That leads to obtaining data simultaneously from an increased number of data sources, to widening the frequency range and to significant complexity reductions. In particular, research has been done in the directions of: (1) asymmetric data compression/ reconstruction; (2) data acquisition from sources in the GHz frequency range; (3) rational acquisition of impedance data; (4) data acquisition based on signal and sine wave reference function crossings. Microelectronic implementation of the research results is considered. In particular, FPGA implementation of a FastDFT processor has been developed and tested.