2009
DOI: 10.1109/jsen.2009.2033199
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An Area-Efficient and Low-Power Logarithmic A/D Converter for Current-Mode Sensor Array

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Cited by 7 publications
(4 citation statements)
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“…Both exponential and logarithmic ADCs have the possibility to expand dynamic range and let to quantize the input with less number of physical bits in comparison with linear ADCs. These nonlinear data conversion techniques lead to some advantages, such as lower power consumption, improvement in data conversion efficiency, and less hardware complexity . There are two different structures to quantize neural signals in the literature, which are logarithmic and exponential ADCs, as explained below.…”
Section: Previous Work In Neural Adcsmentioning
confidence: 99%
See 3 more Smart Citations
“…Both exponential and logarithmic ADCs have the possibility to expand dynamic range and let to quantize the input with less number of physical bits in comparison with linear ADCs. These nonlinear data conversion techniques lead to some advantages, such as lower power consumption, improvement in data conversion efficiency, and less hardware complexity . There are two different structures to quantize neural signals in the literature, which are logarithmic and exponential ADCs, as explained below.…”
Section: Previous Work In Neural Adcsmentioning
confidence: 99%
“…Unlike conventional linear ADCs that linearly map the analog signal to its digital representation and perform the data compression by post signal processing, nonlinear ADCs can directly convert and compress input signal by means of nonlinear encoding. 22 In a conventional linear ADC, code width is uniform over the entire input range. Logarithmic ADCs, as the nonlinear ones, have different code width for different inputs, and the code width increases by increasing input, leading to larger quantization error.…”
Section: Previous Work In Neural Adcsmentioning
confidence: 99%
See 2 more Smart Citations