Estimation of signals in colored non gaussian noise based on Gaussian Mixture models

Non-Gaussianity of signals/noise often results in significant performance degradation for systems, which are designed using the Gaussian assumption. So non-Gaussian signals/noise require a different modelling and processing approach. In this paper, we discuss a new Bayesian estimation technique for non-Gaussian signals corrupted by colored non Gaussian noise. The method is based on using zero mean finite Gaussian Mixture Models (GMMs) for signal and noise. The estimation is done using an adaptive non-causal nonlinear filtering technique. The method involves deriving an estimator in terms of the GMM parameters, which are in turn estimated using the EM algorithm. The proposed filter is of finite length and offers computational feasibility. The simulations show that the proposed method gives a significant improvement compared to the linear filter for a wide variety of noise conditions, including impulsive noise. We also claim that the estimation of signal using the correlation with past and future samples leads to reduced mean squared error as compared to signal estimation based on past samples only.

A suprathreshold stochastic resonance based pre-processor for direction-of-arrival estimation

In this paper we propose a nonlinear preprocessor for enhancing the performance of processors used for direction-of-arrival (DOA) estimation in heavy-tailed non-Gaussian noise. The preprocessor based on the phenomenon of suprathreshold stochastic resonance (SSR), provides SNR gain. The preprocessed data is used for DOA estimation by the MUSIC algorithm. Simulation results are presented to show that the SSR preprocessor provides a significant improvement in the performance of MUSIC in heavy-tailed noise at low SNR.

An analytical model for the capacity estimation of combined VoIP and TCP file transfers over EDCA in an IEEE 802.11e WLAN

In this paper we develop and numerically explore the modeling heuristic of using saturation attempt probabilities as state dependent attempt probabilities in an IEEE 802.11e infrastructure network carrying packet telephone calls and TCP controlled file downloads, using Enhanced Distributed Channel Access (EDCA). We build upon the fixed point analysis and performance insights in [1]. When there are a certain number of nodes of each class contending for the channel (i.e., have nonempty queues), then their attempt probabilities are taken to be those obtained from saturation analysis for that number of nodes. Then we model the system queue dynamics at the network nodes. With the proposed heuristic, the system evolution at channel slot boundaries becomes a Markov renewal process, and regenerative analysis yields the desired performance measures.The results obtained from this approach match well with ns2 simulations. We find that, with the default IEEE 802.11e EDCA parameters for AC 1 and AC 3, the voice call capacity decreases if even one file download is initiated by some station. Subsequently, reducing the voice calls increases the file download capacity almost linearly (by 1/3 Mbps per voice call for the 11 Mbps PHY).

Elastic property estimation using Ultrasound Assisted Optical Elastography through Remote Palpation - A simulation study - art. no. 61640Q

We propose an effective elastography technique in which an acoustic radiation force is used for remote palpation to generate localized tissue displacements, which are directly correlated to localized variations of tissue stiffness and are measured using a light probe in the same direction of ultrasound propagation. The experimental geometry has provision to input light beam along the ultrasound propagation direction, and hence it can be prealigned to ensure proper interception of the focal region by the light beam. Tissue-mimicking phantoms with homogeneous and isotropic mechanical properties of normal and malignant breast tissue are considered for the study. Each phantom is insonified by a focusing ultrasound transducer (1 MHz). The focal volume of the transducer and the ultrasound radiation force in the region are estimated through solving acoustic wave propagation through medium assuming average acoustic properties. The forward elastography problem is solved for the region of insonification assuming the Lame's parameters and Poisson's ratio, under Dirichlet boundary conditions which gives a distribution of displacement vectors. The direction of displacement, though presented spatial variation, is predominantly towards the ultrasound propagation direction. Using Monte Carlo (MC) simulation we have traced the photons through the phantom and collected the photons arriving at the detector on the boundary of the object in the direction of ultrasound. The intensity correlations are then computed from detected photons. The intensity correlation function computed through MC simulation showed a modulation whose strength is found to be proportional to the amplitude of displacement and inversely related to the storage (elastic) modulus. It is observed that when the storage modulus in the focal region is increased the computed displacement magnitude, as indicated by the depth of modulation in the intensity autocorrelation, decreased and the trend is approximately exponential.

Nonlinear Sliding Mode Control Design for an Air-breathing Engine with State Estimation

A modern system theory based nonlinear control design is discussed in this paper for successful operation of an air-breathing engine operating at supersonic speed. The primary objective of the control design of such an air-breathing engine is to ensure that the engine dynamically produces the thrust that tracks a commanded value of thrust as closely as possible by regulating the fuel flow to the combustion system. However, since the engine operates in the supersonic range, an important secondary objective is to manage the shock wave configuration in the intake section of the engine which is manipulated by varying the throat area of the nozzle. A nonlinear sliding mode control technique has been successfully used to achieve both of the above objectives. In this problem, since the process is faster than the actuators, independent control designs are also carried out for the actuators as well to assure the satisfactory performance of the system. Moreover, to filter out the sensor and process noises and to estimate the states for making the control design operate based on output feedback, an Extended Kalman Filter based state estimation design is also carried out. The promising simulation results suggest that the proposed control design approach is quite successful in obtaining robust performance of the air-breathing engine.

Reliability models for existing structures based on dynamic state estimation and data based asymptotic extreme value analysis

The problem of time variant reliability analysis of existing structures subjected to stationary random dynamic excitations is considered. The study assumes that samples of dynamic response of the structure, under the action of external excitations, have been measured at a set of sparse points on the structure. The utilization of these measurements m in updating reliability models, postulated prior to making any measurements, is considered. This is achieved by using dynamic state estimation methods which combine results from Markov process theory and Bayes' theorem. The uncertainties present in measurements as well as in the postulated model for the structural behaviour are accounted for. The samples of external excitations are taken to emanate from known stochastic models and allowance is made for ability (or lack of it) to measure the applied excitations. The future reliability of the structure is modeled using expected structural response conditioned on all the measurements made. This expected response is shown to have a time varying mean and a random component that can be treated as being weakly stationary. For linear systems, an approximate analytical solution for the problem of reliability model updating is obtained by combining theories of discrete Kalman filter and level crossing statistics. For the case of nonlinear systems, the problem is tackled by combining particle filtering strategies with data based extreme value analysis. In all these studies, the governing stochastic differential equations are discretized using the strong forms of Ito-Taylor's discretization schemes. The possibility of using conditional simulation strategies, when applied external actions are measured, is also considered. The proposed procedures are exemplifiedmby considering the reliability analysis of a few low-dimensional dynamical systems based on synthetically generated measurement data. The performance of the procedures developed is also assessed based on a limited amount of pertinent Monte Carlo simulations. (C) 2010 Elsevier Ltd. All rights reserved.

Dust aerosols over India and adjacent continents retrieved using METEOSAT infrared radiance Part II: quantification of wind dependence and estimation of radiative forcing

Long-range transport of continental dust makes these particles a significant constituent even at locations far from their sources. It is important to study the temporal variations in dust loading over desert regions and the role of meteorology, in order to assess its radiative impact. In this paper, infrared radiance (10.5-12.5 mu m), acquired by the METEOSAT-5 satellite (similar to 5-km resolution) during 1999 and 2003 was used to quantify wind dependence of dust aerosols and to estimate the radiative forcing. Our analysis shows that the frequency of occurrence of dust events was higher during 2003 compared to 1999. Since the dust production function depends mainly on the surface wind speed over regions which are dry and without vegetation, the role of surface wind on IDDI was examined in detail. It was found that an increase of IDDI with wind speed was nearly linear and the rate of increase in IDDI with surface wind was higher during 2003 compared to 1999. It was also observed that over the Indian desert, when wind speed was the highest during monsoon months (June to August), the dust production rate was lower because of higher soil moisture (due to monsoon rainfall). Over the Arabian deserts, when the wind speed is the highest during June to August, the dust production rate is also highest, as soil moisture is lowest during this season. Even though nothing can be said precisely on the reason why 2003 had a greater number of dust events, examination of monthly mean soil moisture at source regions indicates that the occurrence of high winds simultaneous with high soil moisture could be the reason for the decreased dust production efficiency in 1999. It appears that the deserts of Northwest India are more efficient dust sources compared to the deserts of Saudi Arabia and Northeast Africa (excluding Sahara). The radiative impact of dust over various source regions is estimated, and the regionally and annually averaged top of the atmosphere dust radiative forcing (short wave, clear-sky and over land) over the entire study region (0-35 degrees N; 30 degrees-100 degrees E) was in the range of -0.9 to +4.5 W m(-2). The corresponding values at the surface were in the range of -10 to -25 W m(-2). Our studies demonstrate that neglecting the diurnal variation of dust can cause errors in the estimation of long wave dust forcing by as much as 50 to 100%, and nighttime retrieval of dust can significantly reduce the uncertainties. A method to retrieve dust aerosols during nighttime is proposed. The regionally and annually averaged long wave dust radiative forcing was +3.4 +/- 1.6 W m(-2).

Development of a low-cost portable colorimeter for the estimation of fluoride in drinking water

People in many countries are affected by fluorosis owing to the high levels of fluoride in drinking water. An inexpensive method for estimating the concentration of the fluoride ion in drinking water would be helpful in identifying safe sources of water and also in monitoring the performance of defluoridation techniques. For this purpose, a simple, inexpensive, and portable colorimeter has been developed in the present work. It is used in conjunction with the SPADNS method, which shows a color change in the visible region on addition of water containing fluoride to a reagent solution. Groundwater samples were collected from different parts of the state of Karnataka, India and analysed for fluoride. The results obtained using the colorimeter and the double beam spectrophotometer agreed fairly well. The costs of the colorimeter and of the chemicals required per test were about Rs. 250 (US$ 5) and Rs. 2.5 (US$ 0.05), respectively. In addition, the cost of the chemicals required for constructing the calibration curve was about Rs. 15 (US$ 0.3). (C) 2010 Elsevier B.V. All rights reserved.

Optimal Weighted Antenna Selection For Imperfect Channel Knowledge From Training

Receive antenna selection (AS) reduces the hardware complexity of multi-antenna receivers by dynamically connecting an instantaneously best antenna element to the available radio frequency (RF) chain. Due to the hardware constraints, the channels at various antenna elements have to be sounded sequentially to obtain estimates that are required for selecting the ``best'' antenna and for coherently demodulating data. Consequently, the channel state information at different antennas is outdated by different amounts. We show that, for this reason, simply selecting the antenna with the highest estimated channel gain is not optimum. Rather, the channel estimates of different antennas should be weighted differently, depending on the training scheme. We derive closed-form expressions for the symbol error probability (SEP) of AS for MPSK and MQAM in time-varying Rayleigh fading channels for arbitrary selection weights, and validate them with simulations. We then derive an explicit formula for the optimal selection weights that minimize the SEP. We find that when selection weights are not used, the SEP need not improve as the number of antenna elements increases, which is in contrast to the ideal channel estimation case. However, the optimal selection weights remedy this situation and significantly improve performance.

A Training-Based Iterative Detection/Channel Estimation Scheme for Large Non-Orthogonal STBC MIMO Systems

In this paper, we propose a training-based channel estimation scheme for large non-orthogonal space-time block coded (STBC) MIMO systems.The proposed scheme employs a block transmission strategy where an N-t x N-t pilot matrix is sent (for training purposes) followed by several N-t x N-t square data STBC matrices, where Nt is the number of transmit antennas. At the receiver, we iterate between channel estimation (using an MMSE estimator) and detection (using a low-complexity likelihood ascent search (LAS) detector) till convergence or for a fixed number of iterations. Our simulation results show that excellent bit error rate and nearness-to-capacity performance are achieved by the proposed scheme at low complexities. The fact that we could show such good results for large STBCs (e.g., 16 x 16 STBC from cyclic division algebras) operating at spectral efficiencies in excess of 20 bps/Hz (even after accounting for the overheads meant for pilot-based channel estimation and turbo coding) establishes the effectiveness of the proposed scheme.

Experimental estimation of friction force in lubricated cutting of steel

Friction force generated in lubricated cutting of steel is experimentally estimated by recording the tangential force experienced by the spherical face of a pin rubbing against a freshly cut surface. The pin and the cutting tool are both submerged in the lubricant and the pin is situated on the cut-track to record the force. The recording shows an instantaneous achievement of a peak in the force curve followed by a decline in time to a steady state value. The peak and not the steady state friction was found to be sensitive to the structure of the hydrocarbon and addition of additive to the oil. The configuration was designed and tested to demonstrate the influence of a reaction film which develops during cutting, on cutting tool friction. Given the strong correlation between the peak friction and the existence of a tribofilm in the cutting zone, the configuration is used to determine the lower limit of a cutting speed regime, which marks the initiation of lubricant starvation, in cutting of steel using an emulsion as a cutting fluid. (C) 2010 Elsevier B.V. All rights reserved.

Theoretical Estimation of Length Dependent In-Plane Stiffness of Single Walled Carbon Nanotubes Using the Nonlocal Elasticity Theory

In the present paper, Eringen's nonlocal elasticity theory is employed to evaluate the length dependent in-plane stiffness of single-walled carbon nanotubes (SWCNTs). The SWCNT is modeled as an Euler-Bernoulli beam and is analyzed for various boundary conditions to evaluate the length dependent in-plane stiffness. It has been found that the nonlocal scaling parameter has a significant effect on the length dependent in-plane stiffness of SWCNTs. It has been observed that as the nonlocal scale parameter increases the stiffness ratio of SWCNT decreases. In nonlocality, the cantilever SWCNT has high in-plane stiffness as compared to the simply-supported and the clamped cases.

Computer estimation of the Cd---Hg---Te phase diagram

The compounds CdHgTe and its constituent binaries CdTe, HgTe, and CdHg are semiconductors which are used in thermal, infrared, nuclear, thermoelectric and other photo sensitive devices. The compound CdHgTe has a Sphaleritic structure of possible type A1IIB1IIC6VI. The TERCP program of Kaufman is used to estimate the stable regions of the ternary phase diagram using available thermodynamic data. It was found that there was little variation in stochiometry with temperature. The compositions were calculated for temperatures ranging from 325K to 100K and the compositional limits were Cd13−20Hg12−01Te75−79, Hg varying most. By comparison with a similar compound, Cd In2Te4 of forbidden band width. 88 to .90 e.V., similar properties are postulated for Cd1Hg1Te6 with applications in the infra red region of the spectrum at 300K where this composition is given by TERCP at the limit of stability.