Neural signal can be used for clinical disease diagnosis,data analysis and real-time life signal monitoring.Its analysis requires high-performance signal processors.Based on the 180 nm standard CMOS technology,a16-cha...Neural signal can be used for clinical disease diagnosis,data analysis and real-time life signal monitoring.Its analysis requires high-performance signal processors.Based on the 180 nm standard CMOS technology,a16-channel fully-differential neural recording chip is designed.The chip consists of 16-channel low-noise pre-amplifiers,a multiplexer and a successive approximation register（SAR）ADC.The result shows that the equivalent input-referred noise of recording amplifier is 3.63μV,bringing down noise efficiency factor to 4.24.At 8.5 bits effective number of bit（ENOB）,the analog-to-digital converter（ADC）has an SNR of 52.6dB.The core area of the proposed neural recording front-end is about 2.46 mm^2.展开更多
A fourth-order Gm-C Chebyshev low-pass filter is presented as channel selection filter for reconfigurable multi-mode wireless receivers. Low-noise technologies are proposed in optimizing the noise characteristics of b...A fourth-order Gm-C Chebyshev low-pass filter is presented as channel selection filter for reconfigurable multi-mode wireless receivers. Low-noise technologies are proposed in optimizing the noise characteristics of both the Gm cells and the filter topology. A frequency tuning strategy is used by tuning both the transconductance of the Gm cells and the capacitance of the capacitor banks. To achieve accurate cut-off frequencies, an on-chip calibration circuit is presented to compensate for the frequency inaccuracy introduced by process variation. The filter is fabricated in a 0.13 m CMOS process. It exhibits a wide programmable bandwidth from 322.5 k Hz to20 MHz. Measured results show that the filter has low input referred noise of 5.9 n V/（Hz）^（1/2） and high out-of-band IIP3 of 16.2 d Bm. It consumes 4.2 and 9.5 m W from a 1 V power supply at its lowest and highest cut-off frequencies respectively.展开更多
基金Supported by the National Natural Science Foundation of China(61301006,61271113)
文摘Neural signal can be used for clinical disease diagnosis,data analysis and real-time life signal monitoring.Its analysis requires high-performance signal processors.Based on the 180 nm standard CMOS technology,a16-channel fully-differential neural recording chip is designed.The chip consists of 16-channel low-noise pre-amplifiers,a multiplexer and a successive approximation register（SAR）ADC.The result shows that the equivalent input-referred noise of recording amplifier is 3.63μV,bringing down noise efficiency factor to 4.24.At 8.5 bits effective number of bit（ENOB）,the analog-to-digital converter（ADC）has an SNR of 52.6dB.The core area of the proposed neural recording front-end is about 2.46 mm^2.
基金Project supported by the National Natural Science Foundation of China(No.61574045)
文摘A fourth-order Gm-C Chebyshev low-pass filter is presented as channel selection filter for reconfigurable multi-mode wireless receivers. Low-noise technologies are proposed in optimizing the noise characteristics of both the Gm cells and the filter topology. A frequency tuning strategy is used by tuning both the transconductance of the Gm cells and the capacitance of the capacitor banks. To achieve accurate cut-off frequencies, an on-chip calibration circuit is presented to compensate for the frequency inaccuracy introduced by process variation. The filter is fabricated in a 0.13 m CMOS process. It exhibits a wide programmable bandwidth from 322.5 k Hz to20 MHz. Measured results show that the filter has low input referred noise of 5.9 n V/（Hz）^（1/2） and high out-of-band IIP3 of 16.2 d Bm. It consumes 4.2 and 9.5 m W from a 1 V power supply at its lowest and highest cut-off frequencies respectively.
