Comparison of OpAmp based and comparator based switched capacitor filter

Comparator based switched capacitor circuits provide an excellent opportunity to design sampled data systems where the virtual ground condition is detected rather than being continuously forced with negative feedback in Opamp based circuits. This work is an application of this concept to design a 1 st order 330 KHz cutoff frequency Lowpass filter operating at 10 MHz sampling frequency in 0.13μm technology and 1.2 V supply voltage. The Comparator Based Switched Capacitor (CBSC) filter is compared with conventional Two stage Miller compensated Operational amplifier based switched capacitor filter. It is shown that CBSC filter relaxes the constraints like speed ,linearity, gain, stability which would otherwise be hard to satisfy in scaled technologies in Opamp based circuits. The designed CBSC based lowpass filter provides significant power savings compared to traditional Opamp based switched capacitor filter.

A scaled unscented transformation based directed Gaussian sum filter for nonlinear dynamic system identification

Impoverishment of particles, i.e. the discretely simulated sample paths of the process dynamics, poses a major obstacle in employing the particle filters for large dimensional nonlinear system identification. A known route of alleviating this impoverishment, i.e. of using an exponentially increasing ensemble size vis-a-vis the system dimension, remains computationally infeasible in most cases of practical importance. In this work, we explore the possibility of unscented transformation on Gaussian random variables, as incorporated within a scaled Gaussian sum stochastic filter, as a means of applying the nonlinear stochastic filtering theory to higher dimensional structural system identification problems. As an additional strategy to reconcile the evolving process dynamics with the observation history, the proposed filtering scheme also modifies the process model via the incorporation of gain-weighted innovation terms. The reported numerical work on the identification of structural dynamic models of dimension up to 100 is indicative of the potential of the proposed filter in realizing the stated aim of successfully treating relatively larger dimensional filtering problems. (C) 2013 Elsevier Ltd. All rights reserved.

A Kushner-Stratonovich Monte Carlo filter applied to nonlinear dynamical system identification

A Monte Carlo filter, based on the idea of averaging over characteristics and fashioned after a particle-based time-discretized approximation to the Kushner-Stratonovich (KS) nonlinear filtering equation, is proposed. A key aspect of the new filter is the gain-like additive update, designed to approximate the innovation integral in the KS equation and implemented through an annealing-type iterative procedure, which is aimed at rendering the innovation (observation prediction mismatch) for a given time-step to a zero-mean Brownian increment corresponding to the measurement noise. This may be contrasted with the weight-based multiplicative updates in most particle filters that are known to precipitate the numerical problem of weight collapse within a finite-ensemble setting. A study to estimate the a-priori error bounds in the proposed scheme is undertaken. The numerical evidence, presently gathered from the assessed performance of the proposed and a few other competing filters on a class of nonlinear dynamic system identification and target tracking problems, is suggestive of the remarkably improved convergence and accuracy of the new filter. (C) 2013 Elsevier B.V. All rights reserved.

Gammatone Wavelet Cepstral Coefficients for Robust Speech Recognition

We develop noise robust features using Gammatone wavelets derived from the popular Gammatone functions. These wavelets incorporate the characteristics of human peripheral auditory systems, in particular the spatially-varying frequency response of the basilar membrane. We refer to the new features as Gammatone Wavelet Cepstral Coefficients (GWCC). The procedure involved in extracting GWCC from a speech signal is similar to that of the conventional Mel-Frequency Cepstral Coefficients (MFCC) technique, with the difference being in the type of filterbank used. We replace the conventional mel filterbank in MFCC with a Gammatone wavelet filterbank, which we construct using Gammatone wavelets. We also explore the effect of Gammatone filterbank based features (Gammatone Cepstral Coefficients (GCC)) for robust speech recognition. On AURORA 2 database, a comparison of GWCCs and GCCs with MFCCs shows that Gammatone based features yield a better recognition performance at low SNRs.

Sign changes of Fourier coefficients of Hilbert modular forms

Sign changes of Fourier coefficients of various modular forms have been studied. In this paper, we analyze some sign change properties of Fourier coefficients of Hilbert modular forms, under the assumption that all the coefficients are real. The quantitative results on the number of sign changes in short intervals are also discussed. (C) 2014 Elsevier Inc. All rights reserved.

ON THE ROLE OF THE HILBERT TRANSFORM IN BOOSTING THE PERFORMANCE OF THE ANNIHILATING FILTER

We consider the problem of parameter estimation from real-valued multi-tone signals. Such problems arise frequently in spectral estimation. More recently, they have gained new importance in finite-rate-of-innovation signal sampling and reconstruction. The annihilating filter is a key tool for parameter estimation in these problems. The standard annihilating filter design has to be modified to result in accurate estimation when dealing with real sinusoids, particularly because the real-valued nature of the sinusoids must be factored into the annihilating filter design. We show that the constraint on the annihilating filter can be relaxed by making use of the Hilbert transform. We refer to this approach as the Hilbert annihilating filter approach. We show that accurate parameter estimation is possible by this approach. In the single-tone case, the mean-square error performance increases by 6 dB for signal-to-noise ratio (SNR) greater than 0 dB. We also present experimental results in the multi-tone case, which show that a significant improvement (about 6 dB) is obtained when the parameters are close to 0 or pi. In the mid-frequency range, the improvement is about 2 to 3 dB.

MEMS Tunable Optical Filter Based on Multi-Ring Resonator

We propose a novel MEMS tunable optical filter with a flat-top pass band based on multi-ring resonator in an electrostatically actuated microcantilever for communication application. The filter is basically structured on a microcantilever beam and built in optical integrated ring resonator which is placed in one end of the beam to gain maximum stress on the resonator. Thus, when a DC voltage is applied, the beam will bend, that induces a stress and strain in the ring, which brings a change in refractive index and perimeter of the rings leading to change in the output spectrum shift, providing the tenability as high as 0.68nm/mu N. and it is capable of tuning up to 1.7nm.

Exploring sand and bentonite - enhanced sand as filter media for nitrate removal

Increasing nitrate concentrations in ground water is deleterious to human health as ingestion of such water can cause methemoglobinemia in infants and even cancer in adults (desirable limit for nitrate as NO3 - 45 mg/L, IS code 10500-1991). Excess nitrate concentrations in ground water is contributed by reason being disposal of sewage and excessive use of fertilizers. Though numerous technologies such as reverse osmosis, ion exchange, electro-dialysis, permeable reactive barriers using zerovalent iron etc exists, nitrate removal continues to be one of challenging issue as nitrate ion is highly mobile within the soil strata. The tapping the denitrification potential of soil denitrifiers which are inherently available in the soil matrix is the most sustainable approach to mitigate accumulation of nitrate in ground water. The insitu denitrification of sand and bentonite enhanced sand (bentonite content = 5%) in presence of easily assimilable organic carbon such as ethanol was studied. Batch studies showed that nitrate reduction by sand follows first order kinetics with a rate constant 5.3x10(-2) hr(-1) and rate constant 4.3 x 10(-2) hr(-1) was obtained for bentonite-enhanced sand (BS) at 25 degrees C. Filter columns (height = 5 cm and diameter = 8.2 cm) were constructed using sand and bentonite-enhanced sand as filter media. The filtration rate through both the filter columns was maintained at average value of 2.60 cm/h. The nitrate removal rates through both the filter media was assessed for solution containing 22.6 mg NO3-N/L concentrations while keeping C/N mass ratio as 3. For sand filter column, the nitrate removal efficiency reached the average value of 97.6% after passing 50 pore volumes of the nitrate solution. For bentonite-enhanced sand filter column, the average nitrate removal efficiency was 83.5%. The time required for effective operation for sand filter bed was 100 hours, while bentonite-enhanced sand filter bed did not require any maturation period as that of sand filter bed for effective performance because the presence of micropores in bentonite increases the hydraulic retention time of the solution inside the filter bed.

Iterated stochastic filters with additive updates for dynamic system identification: Annealing-type iterations and the filter bank

A nonlinear stochastic filtering scheme based on a Gaussian sum representation of the filtering density and an annealing-type iterative update, which is additive and uses an artificial diffusion parameter, is proposed. The additive nature of the update relieves the problem of weight collapse often encountered with filters employing weighted particle based empirical approximation to the filtering density. The proposed Monte Carlo filter bank conforms in structure to the parent nonlinear filtering (Kushner-Stratonovich) equation and possesses excellent mixing properties enabling adequate exploration of the phase space of the state vector. The performance of the filter bank, presently assessed against a few carefully chosen numerical examples, provide ample evidence of its remarkable performance in terms of filter convergence and estimation accuracy vis-a-vis most other competing filters especially in higher dimensional dynamic system identification problems including cases that may demand estimating relatively minor variations in the parameter values from their reference states. (C) 2014 Elsevier Ltd. All rights reserved.

Spatial filter based light-sheet laser interference technique for three-dimensional nanolithography

We propose a laser interference technique for the fabrication of 3D nano-structures. This is possible with the introduction of specialized spatial filter in a 2 pi cylindrical lens system (consists of two opposing cylindrical lens sharing a common geometrical focus). The spatial filter at the back-aperture of a cylindrical lens gives rise to multiple light-sheet patterns. Two such interfering counter-propagating light-sheet pattern result in periodic 3D nano-pillar structure. This technique overcomes the existing slow point-by-point scanning, and has the ability to pattern selectively over a large volume. The proposed technique allows large-scale fabrication of periodic structures. Computational study shows a field-of-view (patterning volume) of approximately 12: 2mm(3) with the pillar-size of 80 nm and inter-pillar separation of 180 nm. Applications are in nano-waveguides, 3D nano-electronics, photonic crystals, and optical microscopy. (C) 2015 AIP Publishing LLC.

Filter Configuration and PWM Method For Single Phase Inverters with Reduced Conducted EMI Noise

Electromagnetic Interference (EMI) noise is one of the major issues during the design of the grid-tied power converters. Presence of high dv/dt in Common Mode (CM) voltage, excites the parasitic capacitances and causes injection of narrow peaky current to ground. This results in high EMI noise level. A topology consisting of a single phase PWM-rectifier with LCL filter, utilising bipolar PWM method is proposed which reduces the EMI noise level by more than 30dB. This filter topology is shown to be insensitive to the switching delays between the legs of the inverter. The proposed topology eliminates high dv/dt from the dc-bus CM voltage by making it sinusoidal. Hence, the high frequency CM current injection to ground is minimized.

Estimation of intrinsic diffusion coefficients in a pseudo-binary diffusion couple

Major drawback of studying diffusion in multi-component systems is the lack of suitable techniques to estimate the diffusion parameters. In this study, a generalized treatment to determine the intrinsic diffusion coefficients in multi-component systems is developed utilizing the concept of a pseudo-binary approach. This is explained with the help of experimentally developed diffusion profiles in the Cu(Sn, Ga) and Cu(Sn, Si) solid solutions. (C) 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Filter Configuration and PWM Method For Single-Phase Inverters With Reduced Conducted EMI Noise

Electromagnetic interference (EMI) noise is one of the major issues during design of grid-tied power converters. A novel LCL filter topology for a single-phase pulsewidth modulation (PWM) rectifier that makes use of bipolar PWM method is proposed for a single-phase to three-phase motor drive power converter. The proposed topology eliminates high dv/dt from the dc-bus common-mode (CM) voltage by making it sinusoidal. Hence, the high-frequency CM current injection to the ground and the motor-side CM current are minimized. The proposed filter configuration makes the system insensitive to circuit non-idealities such as mismatch in inductors values, unequal turn-on and turn-off delays, and dead-time mismatch between the inverter legs. Different variants of the filter topology are compared to establish the effectiveness of the proposed circuit. Experimental results based on the EMI measurement on the grid side and the CM current measurement on the motor side are presented for a 5-kW motor drive. It is shown that the proposed filter topology reduces the EMI noise level by about 35 dB.

Role of the Molar Volume on Estimated Diffusion Coefficients

The role of the molar volume on the estimated diffusion parameters has been speculated for decades. The Matano-Boltzmann method was the first to be developed for the estimation of the variation of the interdiffusion coefficients with composition. However, this could be used only when the molar volume varies ideally or remains constant. Although there are no such systems, this method is still being used to consider the ideal variation. More efficient methods were developed by Sauer-Freise, Den Broeder, and Wagner to tackle this problem. However, there is a lack of research indicating the most efficient method. We have shown that Wagner's method is the most suitable one when the molar volume deviates from the ideal value. Similarly, there are two methods for the estimation of the ratio of intrinsic diffusion coefficients at the Kirkendall marker plane proposed by Heumann and van Loo. The Heumann method, like the Matano-Boltzmann method, is suitable to use only when the molar volume varies more or less ideally or remains constant. In most of the real systems, where molar volume deviates from the ideality, it is safe to use the van Loo method. We have shown that the Heumann method introduces large errors even for a very small deviation of the molar volume from the ideal value. On the other hand, the van Loo method is relatively less sensitive to it. Overall, the estimation of the intrinsic diffusion coefficient is more sensitive than the interdiffusion coefficient.