Pseudo Gaussian Research Articles

Sensing system with an artificial neural network based on floating-gate metal oxide semiconductor transistors

This paper shows a novel design of a gas sensor system based on artificial neural networks and Floating-gate MOS Transistors (FGMOS). Two types of circuits with FGMOS transistors of minimum dimensions were designed and simulated by Simulink of Matlab; simulations and experimental measurements results were compared obtaining good expectations. The reason of using FGMOS is that ANN can also be implemented with these kinds of devices, since ANN’s based on FGMOS are able to produce pseudo Gaussian-functions. These functions give a reliable option to determine the gas concentration. A sensitive thin film can be deposited on the FGMOS’s floating gate, which produces a charge variation due to the chemical reaction between the sensitive layer and the gas species, modifying the threshold voltage thereby a correlation of drain current of the FGMOS with gas concentration can be obtained. Therefore, a generator circuit was implemented for the pseudo Gaussian signal with FGMOS. This system can be applied in environments with dangerous species such as CO2, CO, methane, propane, among others. Simulations demonstrated that the implemented proposal has a good performance as an alternative method for sensing gas concentrations, compared with conventional sensors.

Investigation of low current gas tungsten arc welding using split anode calorimetry

Most previous split anode calorimetry research has applied high weld currents which exhibit pseudo Gaussian distributions of arc current and power density. In this paper we investigate low current arcs and show that both the current and power distributions have minima in the centre – varying significantly from the expected Gaussian profile. This was postulated due to the formation of the arc with the copper anode and the tungsten cathode. Furthermore, a number of parameters were varied including the step size between measurements, anode thickness and anode surface condition as well as cathode type and tip geometry. The step size between measurements significantly influenced the distribution profile and the anode thickness needed to be above 7 mm to obtain consistent results.

Novel orthogonal velocity polishing tool and its material removal characteristics from CVD SiC mirror surfaces.

A new and patented polishing tool called Orthogonal Velocity field Tool (OVT) was built and its material removal characteristics from Chemical Vapor Deposition Silicon Carbide (CVD SiC) mirror surfaces were investigated in this study. The velocity field of OVT is produced by rotating the bicycle type tool in the two orthogonal axes, and this concept is capable of producing a material removal foot print of pseudo Gaussian shapes. First for the OVT characterization, we derived a theoretical material removal model using distributions of pressure exerted onto the workpiece surface, relative speed between the tool and workpiece surface, and dwell time inside the tool- workpiece contact area. Second, using two flat CVD SiC mirrors that are 150 mm in diameter, we ran material removal experiments over machine run parameter ranging from 12.901 to 25.867 psi in pressure, from 0.086 m/sec to 0.147 m/sec tool in the relative speed, and 5 to 15 sec in dwell time. Material removal coefficients are obtained by using the in-house developed data analysis program. The resulting material removal coefficient varies from 3.35 to 9.46 um/psi hour m/sec with a mean value of 5.90 ± 1.26(standard deviation). We describe the technical details of the new OVT machine, the data analysis program, the experiments, and the results together with the implications to the future development of the machine.

An adaptive bandwidth nonlocal means image denoising in wavelet domain

This paper proposes a new wavelet domain denoising algorithm. In the results of conventional wavelet domain denoising methods, ringing artifacts or wavelet-shaped noises are sometimes observed due to thresholding of small but important coefficients or due to generation of large coefficients in flat areas. In this paper, nonlocal means filtering is applied to each subband of wavelet decomposition, which can keep small coefficients and does not generate unwanted large coefficients. Since the performance of nonlocal means filtering depends on the appropriate kernel bandwidth, we also propose a method to find global and local kernel bandwidth for each subband. In comparison with conventional methods, the proposed method shows lower PSNR than BM3D when pseudo white Gaussian noise is added, but higher PSNR than the spatial nonlocal means filtering and wavelet thresholding methods. For the mixture noise or Poisson noise, which may better explain the real noise from camera sensors, the proposed method shows better or comparable results than the state-of-the-art methods. Also, it is believed that the proposed method shows better subjective quality for the noisy images captured in the low-illumination conditions.

Identification of Objectionable Audio Segments Based on Pseudo and Heterogeneous Mixture Models

In this paper, we generalize the Gaussian Mixture Model (GMM) in two ways: a) by introducing novel distance measures between two vectors based on nonlinear maps to give more general mixture models; b) by building mixture models based on multiple different kinds of distributions. These two generalizations cope with different problems arisen in feature modeling. Mixture model obtained by first method is called pseudo Gaussian Mixture Model (pseudo GMM). Compared to the traditional GMM, pseudo GMM with nonlinear maps have better performance on nonlinear problems, while the computational complexity is almost the same as the Expectation-Maximization (EM) algorithm for traditional GMM according to the iteration procedures. The second generalization considers that in practice the practical learning problem often involves multiple, heterogeneous data sources, while classical mixture models are based on a single kind of distribution. In this work, we consider heterogeneous mixture models (hetMM) based on multiple different kinds of distributions. Different types of distributions in hetMM may have quite different properties and may capture different features of the data. Component classifiers including pseudo and hetMM based classifiers are employed in our task of erotic audio recognition. Experimental results with classifiers built based on pseudo GMM and hetMM for erotic audio recognition demonstrate the effectiveness of the proposed model. Online and off-line experiments show that the proposed approach is highly effective for erotic audio recognition.

Extraction of reference lines and items from form document images with complicated background

The extraction of reference lines and items is a fundamental and crucial task in form document analysis. Most of the studies performed so far were done in connection with binary images. This paper proposes a method of extracting lines from gray-level images, by constructing a 2D pseudo Gaussian–Coiflet wavelet with adjustable rectangular support. We also present a method of extracting items using the extracted reference lines and multiresolution wavelet sub-images, which is independent of the intensity of the strokes and backgrounds. The experimental results demonstrate the effectiveness of our proposed methods.

Extraction of reference lines and items from form document images with complicated background

Abstract The extraction of reference lines and items is a fundamental and crucial task in form document analysis. Most of the studies performed so far were done in connection with binary images. This paper proposes a method of extracting lines from gray-level images, by constructing a 2D pseudo Gaussian–Coiflet wavelet with adjustable rectangular support. We also present a method of extracting items using the extracted reference lines and multiresolution wavelet sub-images, which is independent of the intensity of the strokes and backgrounds. The experimental results demonstrate the effectiveness of our proposed methods.

Determining the effect of hydration upon the properties of ligaments using pseudo Gaussian stress stimuli

The level of tissue hydration is known to effect viscoelastic material properties. However, prior studies have not fully investigated the effect of hydration on dynamic behavior nor compared the results of transient and dynamic behavior. The material properties of medial collateral rat knee ligaments were studied in relation to hydration, using (sequentially) 0.3 osmolar artificial interstitial fluid (AIF), solutions of AIF plus sucrose with osmolarity 1.05, 1.80 or 2.55, and then AIF. In each solution, the complex compliance was determined as a function of frequency, and the creep response was measured. Complex compliance was determined from a constitutive model created by applying a 0.4±0.2 MPa pseudo Gaussian (PGN) stress stimulus to the ligament. Dehydration caused a reduction in cross-sectional area that was linearly related to the osmolarity of the solution. Reductions of up to 52% were observed and were reversible upon rehydration. Dehydration caused a reduction in the creep rate that was not immediately recovered upon rehydration. The storage compliance was reduced by up to 50% with dehydration; these changes were reversed upon rehydration. The loss compliance and phase angle were not affected by dehydration. Transient and dynamic experiments examine different viscoelastic characteristics and both types of tests appear to be necessary to fully characterize the effects of hydration.

Properties of mouse cutaneous rapidly adapting afferents: relationship to skin viscoelasticity.

When skin is stretched, stimuli experienced by a cutaneous mechanoreceptor neuron are transmitted to the nerve ending through the skin. In these experiments, we tested the hypothesis that the viscoelastic response of the skin influences the dynamic response of cutaneous rapidly adapting (RA) neurons. Cutaneous RA afferent neurons were recorded in 3 species of mice (Tsk, Pallid, and C57BL6) whose skin has different viscoelastic properties. Isolated samples of skin and nerve were stimulated mechanically with a dynamic stretch stimulus, which followed a pseudo Gaussian waveform with a bandwidth of 0-60 Hz. The mechanical response of the skin was measured as were responses of single RA cutaneous mechanoreceptor neurons. For each neuron, the strength of association between spike responses and the dynamic and static components of stimuli were determined with multiple logistic regression analysis. The viscoelastic material properties of each skin sample were determined indirectly, by creating a nonlinear (Wiener-Volterra) model of the stress-strain relationship, and using the model to predict the complex compliance (i.e., the viscoelastic material properties). The dynamic sensitivity of RA mechanoreceptor neurons in mouse hairy skin was weakly related to the viscoelastic properties of the skin. Loss modulus and phase angle were lower (indicating a decreased viscous component of response) in Tsk and Pallid than in C57BL6 mice. However, RA mechanoreceptor neurons in Tsk and Pallid skin did not differ from those in C57 skin with regard to their sensitivity to the rate of change of stress or to the rate of change of incremental strain energy. They did have a decreased sensitivity to the rate of change of tensile strain. Thus the skin samples with lower dynamic mechanical response contained neurons with a somewhat lower sensitivity to dynamic stimuli.

Optimal filtering of nonlinear systems based on pseudo gaussian densities

We consider the problem of estimating the state of a discrete-time dynamic system comprising a linear system equation and a nonlinear measurement equation based on measurements corrupted by non-Gaussian noise. The problem is solved by recursively calculating the complete posterior density of the state given the measurements. For representing the resulting non-Gaussian posterior, a new exponential type density, the so called pseudo Gaussian density, is introduced. By converting the original nonlinear system to an equivalent linear representation in a higher-dimensional space, the parameters of the pseudo Gaussian posterior are obtained by means of a linear estimator operating in the higher-dimensional space. The resulting filtering algorithms are easy to implement and always guarantee valid posterior densities.

連想記憶の想起過程における内部電位の確率密度

Recalling process of associative memory on the Little-Hopfield model is formulated based on an assumption that distortions of probability density of the inner potential from normal distribution are caused by self-correlations. The overlap (direction cosine) is formulated as an expected value of output function in terms of a pseudo Gaussian probability density. It is shown that the probability density as well as the overlap is in good agreement with simulations for various output functions including a non-monotone function.

OPTIMIZING MODELS OF DOLPHIN AUDITORY SENSITIVITY USING EVOLUTIONARY COMPUTATION

ABSTRACT Object classifiers that attempt to mimic dolphin echolocation require an auditory weighting function representative of dolphin peripheral auditory processing. An evolutionary program (EvPg) was used to fit the frequency-dependent output of a bank of bandpass filters to the auditory sensitivity of the bottlenose dolphin, Tursiops truncatus. Pseudo-Gaussian (PG) and rounded exponential (ROEX) functions were used to describe individual filter shapes. Variables determining the number of filters per model, overall filter shape and amplitude scaling were submitted to the EvPg for optimization. Maximum deviation (P e ) between model output and the sensitivity of the dolphin was used as a measure of similarity between the two, i.e., lower P e indicated a greater similarity. The number of filters converged upon 37 for all ROEX models and ≤ 45 for all PG models. The P e of the best-performing PG model was 0.08, and for all ROEX models was 0.13. Greatest deviations typically occurred below 5 kHz and above 130 kHz. Relative audiometric sensitivity of a dolphin ear model has been improved relative to previous models, thereby providing an auditory weighting function more representative of dolphin peripheral auditory processing. This model will be applied to further investigate how dolphins use echolocation to discriminate among objects.

Radial semiconductor drift chambers

The conditions under which the energy resolution of a radial semiconductor drift chamber based detector system becomes dominated by the step noise from the detector dark current have been investigated. To minimise the drift chamber dark current attention should be paid to carrier generation at Si/SiO 2 interfaces. This consideration conflicts with the desire to reduce the signal risetime: a higher drift field for shorter signal pulses requires a larger area of SiO 2. Calculations for the single shaping and pseudo Gaussian passive filters indicate that for the same degree of signal risetime sensitivity in a system dominated by the step noise from the detector dark current, the pseudo Gaussian filter gives only a 3% improvement in signal/noise and 12% improvement in rate capability compared with the single shaper performance.

Efficient Generation of Statistically Good Pseudonoise by Linearly Interconnected Shift Registers

Some new algorithms are presented for efficiently generating pseudorandom noise both in hardware and software. In software, a new word of pseudorandom bits can be generated about every 12 machine cycles, and hardware implementations can generate pseudo Gaussian noise with bandwith of 20 MHz or more. The algorithms generate binary maximal-length linear recursive sequencies of high degree and with many nonzero terms. The ability to efficiently implement high-degree recursions is important because the number of consecutive bits which can be guaranteed to be both linearly and statistically independent is equal to the degree of the recursion. The implementations are by interconnection of several short shift registers in a linear manner in such a way that different widely spaced phase shifts of the same p-n sequence appear in the stages of the several registers. Some specific algorithms have been subjected to extensive statistical evaluation, with no evidence found to distinguish the sequences from purely random binary sequences.