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This brief presents a linearization technique for open-loop amplifiers. It utilizes the exponential ${V}{-}{I}$ transfer of MOS transistors in weak-inversion together with a weak form of resistive degeneration. By using a specific relationship between the input transconductance and the source degeneration resistance, the amplifier is shown to have a significant reduction ( $\sim 50\times $ ) in its third-order distortion component. Based on this linearization principle, two amplifier topologies are proposed by implementing the degeneration in (a) pseudo-differential and (b) common-mode configuration. The pseudo-differential degeneration scheme allows the amplifier to achieve more than 80dB linearity for 150mV $_{\text {pp-diff}}$ input swing at the expense of 35% lower power-efficiency. The common-mode degeneration eliminates this power penalty but exhibits ~10dB worse linearity. To ensure an optimal linearity over process variation, a foreground calibration scheme is used to detect the nonlinearity. The nonlinearity correction is done by adjusting the bias current of the amplifier. The proof-of-concept amplifiers are constructed on a stripboard to demonstrate the effectiveness of the proposed linearization technique. With an input signal of 50mV $_{\rm pp{-}diff}$ , the two topologies achieve −105dB and −95dB HD3, respectively, improving the linearity of the state-of-the-art open-loop amplifiers by at least 30dB.

This paper presents a closed-loop class-AB residue amplifier for pipelined analog-to-digital converters (ADCs). It consists of a push–pull structure with a “split-capacitor” biasing circuit that enhances its power efficiency. The amplifier is inherently quite linear, and so incomplete settling can be used to save power while still maintaining sufficient linearity. This also allows the amplifier’s gain to be corrected by adjusting its bias current. When combined with digital gain-error detection, in this case the split-ADC technique, the result is a power-efficient gain calibration scheme. In a prototype pipelined ADC, this scheme converges in only 12 000 clock cycles. With a near-Nyquist input, the ADC achieves 66-dB SNDR and 77.3-dB SFDR at 53 MS/s. Implemented in 40-nm CMOS, it dissipates 9 mW, of which 0.83 mW is consumed in the residue amplifiers. This represents a 1.8 $\times $ improvement in power efficiency compared to state-of-the-art class-AB residue amplifiers.

This paper presents a new dynamic residue amplifier topology for pipelined analog-to-digital converters. With an input signal of 100 mVpp,diff and 4 $\times$ gain, it achieves −100-dB total harmonic distortion, the lowest ever reported for a dynamic amplifier. Compared to the state of the art, it exhibits 25 dB better linearity with twice the output swing and similar noise performance. The key to this performance is a new linearization technique based on capacitive degeneration, which exploits the exponential voltage-to-current relationship of MOSFET in weak inversion. The prototype amplifier is fabricated in a 28-nm CMOS process and dissipates only 87 $\mu \text{W}$ at a clock speed of 43 MS/s, thereby improving the energy per cycle by 26 $\times$ compared with that of state-of-the-art high-linearity amplifiers.

This paper presents a new dynamic residue amplifier for pipelined ADCs. With an input of 100mV pp, diff and 4x gain, it achieves −100dB THD, the lowest ever reported in dynamic amplifiers. Compared to the state-of-the-art, it exhibits >25dB better linearity with >2x larger output swing and similar noise performance. The key to this is a new linearization technique based on capacitive-degeneration. Fabricated in a 28nm CMOS, the prototype amplifier dissipates 87μW at a clock speed of 43MS/s and maintains −100dB THD up to 150MS/s.

Hyperlipidemia is an important modifiable risk factor contributing to atterosclerosis in diabetes mellitus. Zingiber officinale (ginger) widely consumed as spice is known for its hypoglycemic and hypochlosteremic actions. The present study was undertaken to investigate anti-hyperlipidemic action of ginger juice in alloxan-induced diabetic rats. Male Wister rats, 130-150 g wt, fed on standard diet and water ad libitum were divided into 4 groups (n=6 in each group): group I nondiabetic control, group II non-diabetic treated; group III diabetic control and group IV diabetic treated. Diabetes was induced by Inj. alloxan 150 mg Kg–1 b.w., i.p. (group III & IV) on Day 2. Rats having blood glucose level of >7 mmol/l on day 5 (72 hrs after alloxan Inj.) were considered diabetic and selected for experimentation. Both non-diabetic and diabetic treated groups (Gr II & IV) received Zingiber officinale (ginger) juice (4 ml Kg–1 b.w., p.o.) for 10 days (day 2-day 11) through Ryles tube. On Day 12, animals were sacrificed under light ether anaesthesia, blood was collected by cardiac puncture and serum separated for estimation of lipids. Zingiber officinale (ginger) juice significantly (p

This paper presents an effective algorithm for human identification using time and frequency domain features extracted from electrocardiogram (ECG) signal. Instead of directly using the ECG data of a person as the feature, first, it is shown that a few number of reflection coefficients extracted from the autocorrelation function of the data can efficiently perform the recognition task. In frequency domain, discrete cosine transform (DCT) based feature is employed, which offers even a better recognition performance. It is found that the proposed time and frequency domain features demonstrate a high within class compactness and between class separability. Prior to feature extraction, a pre-processing scheme is incorporated to reduce the effect of different noises and artifacts. For the purpose of recognition, a linear discriminant based classifier is employed, where the two features are jointly utilized. The proposed human identification scheme has been tested on standard ECG databases and high recognition accuracy is achieved with an extremely low feature dimension.