A mixed-split scheme for 2-D DPCM based LSF quantization

In this paper a mixed-split scheme is proposed in the context of 2-D DPCM based LSF quantization scheme employing split vector product VQ mechanism. Experimental evaluation shows that the new scheme is successfully being able to show better distortion performance than existing safety-net scheme for noisy channel even at considerably lower search complexity, by efficiently exploiting LSF trajectory behavior across the consecutive speech frames.

Role of predictors in downscaling surface temperature to river basin in India for IPCC SRES scenarios using support vector machine

In this paper, downscaling models are developed using a support vector machine (SVM) for obtaining projections of monthly mean maximum and minimum temperatures (T-max and T-min) to river-basin scale. The effectiveness of the model is demonstrated through application to downscale the predictands for the catchment of the Malaprabha reservoir in India, which is considered to be a climatically sensitive region. The probable predictor variables are extracted from (1) the National Centers for Environmental Prediction (NCEP) reanalysis dataset for the period 1978-2000, and (2) the simulations from the third-generation Canadian Coupled Global Climate Model (CGCM3) for emission scenarios A1B, A2, B1 and COMMIT for the period 1978-2100. The predictor variables are classified into three groups, namely A, B and C. Large-scale atmospheric variables Such as air temperature, zonal and meridional wind velocities at 925 nib which are often used for downscaling temperature are considered as predictors in Group A. Surface flux variables such as latent heat (LH), sensible heat, shortwave radiation and longwave radiation fluxes, which control temperature of the Earth's surface are tried as plausible predictors in Group B. Group C comprises of all the predictor variables in both the Groups A and B. The scatter plots and cross-correlations are used for verifying the reliability of the simulation of the predictor variables by the CGCM3 and to Study the predictor-predictand relationships. The impact of trend in predictor variables on downscaled temperature was studied. The predictor, air temperature at 925 mb showed an increasing trend, while the rest of the predictors showed no trend. The performance of the SVM models that are developed, one for each combination of predictor group, predictand, calibration period and location-based stratification (land, land and ocean) of climate variables, was evaluated. In general, the models which use predictor variables pertaining to land surface improved the performance of SVM models for downscaling T-max and T-min

A frame-invariant scheme for the geometrically exact beam using rotation vector parametrization

While frame-invariant solutions for arbitrarily large rotational deformations have been reported through the orthogonal matrix parametrization, derivation of such solutions purely through a rotation vector parametrization, which uses only three parameters and provides a parsimonious storage of rotations, is novel and constitutes the subject of this paper. In particular, we employ interpolations of relative rotations and a new rotation vector update for a strain-objective finite element formulation in the material framework. We show that the update provides either the desired rotation vector or its complement. This rules out an additive interpolation of total rotation vectors at the nodes. Hence, interpolations of relative rotation vectors are used. Through numerical examples, we show that combining the proposed update with interpolations of relative rotations yields frame-invariant and path-independent numerical solutions. Advantages of the present approach vis-a-vis the updated Lagrangian formulation are also analyzed.

Analysis Of The Energy Quantization Effects On Single Electron Inverter Performance Through Noise Margin Modeling

Possible integration of Single Electron Transistor (SET) with CMOS technology is making the study of semiconductor SET more important than the metallic SET and consequently, the study of energy quantization effects on semiconductor SET devices and circuits is gaining significance. In this paper, for the first time, the effects of energy quantization on SET inverter performance are examined through analytical modeling and Monte Carlo simulations. It is observed that the primary effect of energy quantization is to change the Coulomb Blockade region and drain current of SET devices and as a result affects the noise margin, power dissipation, and the propagation delay of SET inverter. A new model for the noise margin of SET inverter is proposed which includes the energy quantization effects. Using the noise margin as a metric, the robustness of SET inverter is studied against the effects of energy quantization. It is shown that SET inverter designed with CT : CG = 1/3 (where CT and CG are tunnel junction and gate capacitances respectively) offers maximum robustness against energy quantization.

Prediction of Ultimate Capacity of Laterally Loaded Piles in Clay: A Relevance Vector Machine Approach

This study investigates the potential of Relevance Vector Machine (RVM)-based approach to predict the ultimate capacity of laterally loaded pile in clay. RVM is a sparse approximate Bayesian kernel method. It can be seen as a probabilistic version of support vector machine. It provides much sparser regressors without compromising performance, and kernel bases give a small but worthwhile improvement in performance. RVM model outperforms the two other models based on root-mean-square-error (RMSE) and mean-absolute-error (MAE) performance criteria. It also stimates the prediction variance. The results presented in this paper clearly highlight that the RVM is a robust tool for prediction Of ultimate capacity of laterally loaded piles in clay.

Renormalization of the axial-vector current in QCD

Following the method of Ioffe and Smilga, the propagation of the baryon current in an external constant axial-vector field is considered. The close similarity of the operator-product expansion with and without an external field is shown to arise from the chiral invariance of gauge interactions in perturbation theory. Several sum rules corresponding to various invariants both for the nucleon and the hyperons are derived. The analysis of the sum rules is carried out by two independent methods, one called the ratio method and the other called the continuum method, paying special attention to the nondiagonal transitions induced by the external field between the ground state and excited states. Up to operators of dimension six, two new external-field-induced vacuum expectation values enter the calculations. Previous work determining these expectation values from PCAC (partial conservation of axial-vector current) are utilized. Our determination from the sum rules of the nucleon axial-vector renormalization constant GA, as well as the Cabibbo coupling constants in the SU3-symmetric limit (ms=0), is in reasonable accord with the experimental values. Uncertainties in the analysis are pointed out. The case of broken flavor SU3 symmetry is also considered. While in the ratio method, the results are stable for variation of the fiducial interval of the Borel mass parameter over which the left-hand side and the right-hand side of the sum rules are matched, in the continuum method the results are less stable. Another set of sum rules determines the value of the linear combination 7F-5D to be ≊0, or D/(F+D)≊(7/12). .AE

A Combination of Hexagonal and 12-Sided Polygonal Voltage Space Vector PWM Control for IM Drives Using Cascaded Two-Level Inverters

This paper proposes a multilevel inverter configuration which produces a hexagonal voltage space vector structure in the lower modulation region and a 12-sided polygonal space vector structure in the overmodulation region. A conventional multilevel inverter produces 6n plusmn 1 (n = odd) harmonics in the phase voltage during overmodulation and in the extreme square-wave mode of operation. However, this inverter produces a 12-sided polygonal space vector location, leading to the elimination of 6n plusmn 1 (n = odd) harmonics in the overmodulation region extending to a final 12-step mode of operation with a smooth transition. The benefits of this arrangement are lower losses and reduced torque pulsation in an induction motor drive fed from this converter at higher modulation indexes. The inverter is fabricated by using three conventional cascaded two-level inverters with asymmetric dc-bus voltages. A comparative simulation study of the harmonic distortion in the phase voltage and associated losses in conventional multilevel inverters and that of the proposed inverter is presented in this paper. Experimental validation on a prototype shows that the proposed converter is suitable for high-power applications because of low harmonic distortion and low losses.

A Multilevel Inverter with Hexagonal and 12-sided Polygonal Space Vector Structure for Induction Motor Drive

This paper proposes a multilevel inverter which produces hexagonal voltage space vector structure in lower modulation region and a 12-sided polygonal space vector structure in the over-modulation region. Normal conventional multilevel inverter produces 6n +/- 1 (n=odd) harmonics in the phase voltage during over-modulation and in the extreme square wave mode operation. However, this inverter produces a 12-sided polygonal space vector location leading to the elimination of 6n 1 (n=odd) harmonics in over-modulation region extending to a final 12-step mode operation. The inverter consists of three conventional cascaded two level inverters with asymmetric dc bus voltages. The switching frequency of individual inverters is kept low throughout the modulation index. In the low speed region, hexagonal space phasor based PWM scheme and in the higher modulation region, 12-sided polygonal voltage space vector structure is used. Experimental results presented in this paper shows that the proposed converter is suitable for high power applications because of low harmonic distortion and low switching losses.

Modeling and analysis of energy quantization effects on single electron inverter performance

In this paper, for the first time, the effects of energy quantization on single electron transistor (SET) inverter performance are analyzed through analytical modeling and Monte Carlo simulations. It is shown that energy quantization mainly changes the Coulomb blockade region and drain current of SET devices and thus affects the noise margin, power dissipation, and the propagation delay of SET inverter. A new analytical model for the noise margin of SET inverter is proposed which includes the energy quantization effects. Using the noise margin as a metric, the robustness of SET inverter is studied against the effects of energy quantization. A compact expression is developed for a novel parameter quantization threshold which is introduced for the first time in this paper. Quantization threshold explicitly defines the maximum energy quantization that an SET inverter logic circuit can withstand before its noise margin falls below a specified tolerance level. It is found that SET inverter designed with CT:CG=1/3 (where CT and CG are tunnel junction and gate capacitances, respectively) offers maximum robustness against energy quantization.

Impact of Energy Quantization on the Performance of Current-Biased SET Circuits

The current-biased single electron transistor (SET) (CBS) is an integral part of almost all hybrid CMOS SET circuits. In this paper, for the first time, the effects of energy quantization on the performance of CBS-based circuits are studied through analytical modeling and Monte Carlo simulations. It is demonstrated that energy quantization has no impact on the gain of the CBS characteristics, although it changes the output voltage levels and oscillation periodicity. The effects of energy quantization are further studied for two circuits: negative differential resistance (NDR) and neuron cell, which use the CBS. A new model for the conductance of NDR characteristics is also formulated that includes the energy quantization term.

Distance Relay Co-ordination Using Support Vector Machines in Power Transmission System

In this paper, a new approach to enhance the transmission system distance relay co-ordination is presented. The approach depends on the apparent impedance loci seen by the distance relay during all possible disturbances. In a distance relay, the impedance loci seen at the relay location is obtained by extensive transient stability studies. Support vector machines (SVMs), a class of patterns classifiers are used in discriminating zone settings (zone-1, zone-2 and zone-3) using the signals to be used by the relay. Studies on a sample 9-bus are presented for illustrating the proposed scheme.

Gravitational charges and the quantization of mass

Abstract is not available.

Quantization noise in binary holograms

The signal-to-noise (S/N) ratio in the reconstructed image from a binary hologram has been quantitatively related to the amplitude and phase quantization levels. The S/N ratio increases monotonically with increasing number of quantization levels. This observation is further supported by experimental results.

Effect of fourier domain quantization on matched filtering

It is shown that the use of a coarsely quantized binary digital hologram as a matched filter on an optical computer does not degrade signal-to-noise ratio (SNR) appreciably.

Subspace intersection method of high-resolution bearing estimation in shallow ocean using acoustic vector sensors

The subspace intersection method (SIM) provides unbiased bearing estimates of multiple acoustic sources in a range-independent shallow ocean using a one-dimensional search without prior knowledge of source ranges and depths. The original formulation of this method is based on deployment of a horizontal linear array of hydrophones which measure acoustic pressure. In this paper, we extend SIM to an array of acoustic vector sensors which measure pressure as well as all components of particle velocity. Use of vector sensors reduces the minimum number of sensors required by a factor of 4, and also eliminates the constraint that the intersensor spacing should not exceed half wavelength. The additional information provided by the vector sensors leads to performance enhancement in the form of lower estimation error and higher resolution.