The summer monsoon onset over southern Vietnam is determined through a new criterion based on both in situ daily rainfall at 6 selected stations provided by the Institute of Meteorology and Hydrology, Vietnam, and the zonal component of the wind at 1000hPa from the National Center for Environmental Prediction/Department of Energy reanalysis 2 (NCEP/DOE-II). Over the period 1979-2004, the summer monsoon onset mean date is on 12 May, with a standard deviation of 11.6 days. The temporal and spatial structures of the atmospheric conditions prevailing during the onset period are detailed. Clear changes are seen in the zonal wind (strengthened over the Bay of Bengal and changed from negative to positive over South Vietnam) and in convection (deeper), in association with an intensification of the meridional gradients of sea level pressure at 1000hPa and of moist static energy at 2m over Southeast Asia. The predictability of onset dates is then assessed. Cross validated hindcasts based upon 4 predictors linked to robust signals in the atmospheric dynamics are then provided. They are highly significant when compared to observations (56% of common variance). Basically, late (early) onsets are preceded in March-April by higher (lower) sea level pressure over the East China Sea, stronger (weaker) southeasterly winds over southern Vietnam, decreasing (increasing) deep convection over the Bay of Bengal and the reverse situation over Indonesia (120°E-140°E, 0-10°S).
In this paper, a low-power and low-noise capacitive-coupled chopper instrumentation amplifier (CCIA) is proposed for biopotential sensing applications. A chopping technique is applied to mitigate the domination of flicker noise at low frequency. A new offset cancellation loop is also used to deal with the intrinsic offset, originating from process variation, to reduce ripple noise at the output of CCIA. Moreover, the optimization of the chip area was resolved by adding a T-network capacitor in the negative feedback loop. The CCIA is designed on 0.18 µm process CMOS technology with a total chip area of 0.09 mm2. The post-simulation results show that the proposed architecture can attenuate the output ripple up to 41 dB with a closed-loop gain of 40 dB and up to 800 Hz of bandwidth. The integrated input referred noise (IRN) of the CCIA is 1.8 µVrms over a bandwidth of 200 Hz. A noise efficiency factor (NEF) of 5.4 is obtained with a total power dissipation of 1.2 µW and a supply voltage of 1 V, corresponding to a power efficiency factor of 9.7 that is comparable with that of state-of-the-art studies.
To realize an ultra-low-power and low-noise instrumentation amplifier (IA) for neural and biopotential signal sensing, we investigate two design techniques. The first technique uses a noise-efficient DC servo loop (DSL), which has been shown to be a high noise contributor. The proposed approach offers several advantages: (i) both the electrode offset and the input offset are rejected, (ii) a large capacitor is not needed in the DSL, (iii) by removing the charge dividing effect, the input-referred noise (IRN) is reduced, (iv) the noise from the DSL is further reduced by the gain of the first stage and by the transconductance ratio, and (v) the proposed DSL allows interfacing with a squeezed-inverter (SQI) stage. The proposed technique reduces the noise from the DSL to 12.5% of the overall noise. The second technique is to optimize noise performance using an SQI stage. Because the SQI stage is biased at a saturation limit of 2VDSAT, the bias current can be increased to reduce noise while maintaining low power consumption. The challenge of handling the mismatch in the SQI stage is addressed using a shared common-mode feedback (CMFB) loop, which achieves a common-mode rejection ratio (CMRR) of 105 dB. Using the proposed technique, a capacitively-coupled chopper instrumentation amplifier (CCIA) was fabricated using a 0.18-µm CMOS process. The measured result of the CCIA shows a relatively low noise density of 88 nV/rtHz and an integrated noise of 1.5 µVrms. These results correspond to a favorable noise efficiency factor (NEF) of 5.9 and a power efficiency factor (PEF) of 11.4.
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