AN OPTIMUM SHRINKAGE ESTIMATOR BASED ON MINIMUM-PROBABILITY-OF-ERROR CRITERION AND APPLICATION TO SIGNAL DENOISING

We address the problem of designing an optimal pointwise shrinkage estimator in the transform domain, based on the minimum probability of error (MPE) criterion. We assume an additive model for the noise corrupting the clean signal. The proposed formulation is general in the sense that it can handle various noise distributions. We consider various noise distributions (Gaussian, Student's-t, and Laplacian) and compare the denoising performance of the estimator obtained with the mean-squared error (MSE)-based estimators. The MSE optimization is carried out using an unbiased estimator of the MSE, namely Stein's Unbiased Risk Estimate (SURE). Experimental results show that the MPE estimator outperforms the SURE estimator in terms of SNR of the denoised output, for low (0 -10 dB) and medium values (10 - 20 dB) of the input SNR.

Noise Detected NMR Spectroscopy

Spin noise phenomenon was predicted way back in 1946. However, experimental investigations regarding spin noise became possible only recently with major technological improvements in NMR hardware. These experiments have several potential novel applications and also demand refinements in the existing theoretical framework to explain the phenomenon. Elegance of noise spectroscopy in gathering information about the properties of a system lies in the fact that it does not require external perturbation, and the system remains in thermal equilibrium. Spin noise is intrinsic magnetic fluctuations, and both longitudinal and transverse components have been detected independently in many systems. Detection of fluctuating longitudinal magnetization leads to field of Magnetic Resonance Force Microscopy (MRFM) that can efficiently probe very few spins even down to the level of single spin utilizing ultrasensitive cantilevers. Transverse component of spin noise, which can simultaneously monitor different resonances over a given frequency range enabling one to distinguish between different chemical environments, has also received considerable attention, and found many novel applications. These experiments demand a detailed understanding of the underlying spin noise phenomenon in order to perform perturbation-free magnetic resonance and widen the highly promising application area. Detailed investigations of noise magnetization have been performed recently using force microscopy on equilibrium ensemble of paramagnetic alkali atoms. It was observed that random fluctuations generate spontaneous spin coherences which has similar characteristics as generated by macroscopic magnetization of polarized ensemble in terms of precession and relaxation properties. Several other intrinsic properties like g-factors, isotope-abundance ratios, hyperfine splitting, spin coherence lifetimes etc. also have been achieved without having to excite the sample. In contrast to MRFM-approaches, detection of transverse spin noise also offers novel applications, attracting considerable attention. This has unique advantage as different resonances over a given frequency range enable one to distinguish between different chemical environments. Since these noise signatures scale inversely with sample size, these approaches lead to the possibility of non-perturbative magnetic resonance of small systems down to nano-scale. In this review, these different approaches will be highlighted with main emphasis on transverse spin noise investigations.

Double Gaussian distribution of barrier height observed in densely packed GaN nanorods over Si (111) heterostructures

GaN nanorods were grown by plasma assisted molecular beam epitaxy on intrinsic Si (111) substrates which were characterized by powder X-ray diffraction, field emission scanning electron microscopy, and photoluminescence. The current-voltage characteristics of the GaN nanorods on Si (111) heterojunction were obtained from 138 to 493K which showed the inverted rectification behavior. The I-V characteristics were analyzed in terms of thermionic emission model. The temperature variation of the apparent barrier height and ideality factor along with the non-linearity of the activation energy plot indicated the presence of lateral inhomogeneities in the barrier height. The observed two temperature regimes in Richardson's plot could be well explained by assuming two separate Gaussian distribution of the barrier heights. (C) 2014 AIP Publishing LLC.

Effect of measurement noise on Granger causality

Most of the signals recorded in experiments are inevitably contaminated by measurement noise. Hence, it is important to understand the effect of such noise on estimating causal relations between such signals. A primary tool for estimating causality is Granger causality. Granger causality can be computed by modeling the signal using a bivariate autoregressive (AR) process. In this paper, we greatly extend the previous analysis of the effect of noise by considering a bivariate AR process of general order p. From this analysis, we analytically obtain the dependence of Granger causality on various noise-dependent system parameters. In particular, we show that measurement noise can lead to spurious Granger causality and can suppress true Granger causality. These results are verified numerically. Finally, we show how true causality can be recovered numerically using the Kalman expectation maximization algorithm.

Characterizing the Impact of Feedback Delays on Wideband Rate Adaptation

In contemporary orthogonal frequency division multiplexing (OFDM) systems, such as Long Term Evolution (LTE), LTE-Advanced, and WiMAX, a codeword is transmitted over a group of subcarriers. Since different subcarriers see different channel gains in frequency-selective channels, the modulation and coding scheme (MCS) of the codeword must be selected based on the vector of signal-to-noise-ratios (SNRs) of these subcarriers. Exponential effective SNR mapping (EESM) maps the vector of SNRs into an equivalent flat-fading SNR, and is widely used to simplify this problem. We develop a new analytical framework to characterize the throughput of EESM-based rate adaptation in such wideband channels in the presence of feedback delays. We derive a novel accurate approximation for the throughput as a function of feedback delay. We also propose a novel bivariate gamma distribution to model the time evolution of EESM between the times of estimation and data transmission, which facilitates the analysis. These are then generalized to a multi-cell, multi-user scenario with various frequency-domain schedulers. Unlike prior work, most of which is simulation-based, our framework encompasses both correlated and independent subcarriers and various multiple antenna diversity modes; it is accurate over a wide range of delays.

Origin of 1/f noise in graphene produced for large-scale applications in electronics

The authors report a detailed investigation of the flicker noise (1/f noise) in graphene films obtained from chemical vapour deposition (CVD) and chemical reduction of graphene oxide. The authors find that in the case of polycrystalline graphene films grown by CVD, the grain boundaries and other structural defects are the dominant source of noise by acting as charged trap centres resulting in huge increase in noise as compared with that of exfoliated graphene. A study of the kinetics of defects in hydrazine-reduced graphene oxide (RGO) films as a function of the extent of reduction showed that for longer hydrazine treatment time strong localised crystal defects are introduced in RGO, whereas the RGO with shorter hydrazine treatment showed the presence of large number of mobile defects leading to higher noise amplitude.

A Gaussian network model study suggests that structural fluctuations are higher for inactive states than active states of protein kinases

We performed Gaussian network model based normal mode analysis of 3-dimensional structures of multiple active and inactive forms of protein kinases. In 14 different kinases, a more number of residues (1095) show higher structural fluctuations in inactive states than those in active states (525), suggesting that, in general, mobility of inactive states is higher than active states. This statistically significant difference is consistent with higher crystallographic B-factors and conformational energies for inactive than active states, suggesting lower stability of inactive forms. Only a small number of inactive conformations with the DFG motif in the ``in'' state were found to have fluctuation magnitudes comparable to the active conformation. Therefore our study reports for the first time, intrinsic higher structural fluctuation for almost all inactive conformations compared to the active forms. Regions with higher fluctuations in the inactive states are often localized to the aC-helix, aG-helix and activation loop which are involved in the regulation and/or in structural transitions between active and inactive states. Further analysis of 476 kinase structures involved in interactions with another domain/protein showed that many of the regions with higher inactive-state fluctuation correspond to contact interfaces. We also performed extensive GNM analysis of (i) insulin receptor kinase bound to another protein and (ii) holo and apo forms of active and inactive conformations followed by multi-factor analysis of variance. We conclude that binding of small molecules or other domains/proteins reduce the extent of fluctuation irrespective of active or inactive forms. Finally, we show that the perceived fluctuations serve as a useful input to predict the functional state of a kinase.

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.

Making risk minimization tolerant to label noise

In many applications, the training data, from which one needs to learn a classifier, is corrupted with label noise. Many standard algorithms such as SVM perform poorly in the presence of label noise. In this paper we investigate the robustness of risk minimization to label noise. We prove a sufficient condition on a loss function for the risk minimization under that loss to be tolerant to uniform label noise. We show that the 0-1 loss, sigmoid loss, ramp loss and probit loss satisfy this condition though none of the standard convex loss functions satisfy it. We also prove that, by choosing a sufficiently large value of a parameter in the loss function, the sigmoid loss, ramp loss and probit loss can be made tolerant to nonuniform label noise also if we can assume the classes to be separable under noise-free data distribution. Through extensive empirical studies, we show that risk minimization under the 0-1 loss, the sigmoid loss and the ramp loss has much better robustness to label noise when compared to the SVM algorithm. (C) 2015 Elsevier B.V. All rights reserved.

Acoustic Noise Characterization of Space-Vector Modulated Induction Motor Drives-An Experimental Approach

This paper presents an experimental procedure to determine the acoustic and vibration behavior of an inverter-fed induction motor based on measurements of the current spectrum, acoustic noise spectrum, overall noise in dB, and overall A-weighted noise in dBA. Measurements are carried out on space-vector modulated 8-hp and 3-hp induction motor drives over a range of carrier frequencies at different modulation frequencies. The experimental data help to distinguish between regions of high and low acoustic noise levels. The measurements also bring out the impact of carrier frequency on the acoustic noise. The sensitivity of the overall noise to carrier frequency is indicative of the relative dominance of the high-frequency electromagnetic noise over mechanical and aerodynamic components of noise. Based on the measured current and acoustic noise spectra, the ratio of dynamic deflection on the stator surface to the product of fundamental and harmonic current amplitudes is obtained at each operating point. The variation of this ratio of deflection to current product with carrier frequency indicates the resonant frequency clearly and also gives a measure of the amplification of vibration at frequencies close to the resonant frequency. This ratio is useful to predict the magnitude of acoustic noise corresponding to significant time-harmonic currents flowing in the stator winding.

A common stochastic accumulator with effector-dependent noise can explain eye-hand coordination

The computational architecture that enables the flexible coupling between otherwise independent eye and hand effector systems is not understood. By using a drift diffusion framework, in which variability of the reaction time (RT) distribution scales with mean RT, we tested the ability of a common stochastic accumulator to explain eye-hand coordination. Using a combination of behavior, computational modeling and electromyography, we show how a single stochastic accumulator to threshold, followed by noisy effector-dependent delays, explains eye-hand RT distributions and their correlation, while an alternate independent, interactive eye and hand accumulator model does not. Interestingly, the common accumulator model did not explain the RT distributions of the same subjects when they made eye and hand movements in isolation. Taken together, these data suggest that a dedicated circuit underlies coordinated eye-hand planning.

Zero-Crossings Based Spectrum Sensing Under Noise Uncertainties

In this work, the hypothesis testing problem of spectrum sensing in a cognitive radio is formulated as a Goodness-of-fit test against the general class of noise distributions used in most communications-related applications. A simple, general, and powerful spectrum sensing technique based on the number of weighted zero-crossings in the observations is proposed. For the cases of uniform and exponential weights, an expression for computing the near-optimal detection threshold that meets a given false alarm probability constraint is obtained. The proposed detector is shown to be robust to two commonly encountered types of noise uncertainties, namely, the noise model uncertainty, where the PDF of the noise process is not completely known, and the noise parameter uncertainty, where the parameters associated with the noise PDF are either partially or completely unknown. Simulation results validate our analysis, and illustrate the performance benefits of the proposed technique relative to existing methods, especially in the low SNR regime and in the presence of noise uncertainties.

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.

Study of Wrist Pulse Signals Using a Bi-Modal Gaussian Model

Wrist pulse signals contain important information about the health of a person and hence diagnosis based on pulse signals has assumed great importance. In this paper we demonstrate the efficacy of a two term Gaussian model to extract information from pulse signals. Results have been obtained by conducting experiments on several subjects to record wrist pulse signals for the cases of before exercise and after exercise. Parameters have been extracted from the recorded signals using the model and a paired t-test is performed, which shows that the parameters are significantly different between the two groups. Further, a recursive cluster elimination based support vector machine is used to perform classification between the groups. An average classification accuracy of 99.46% is obtained, along with top classifiers. It is thus shown that the parameters of the Gaussian model show changes across groups and hence the model is effective in distinguishing the changes taking place due to the two different recording conditions. The study has potential applications in healthcare.