Presence Of White Noise Research Articles

Modeling and Adaptive Self-Tuning MVC Control of PAM Manipulator Using Online Observer Optimized with Modified Genetic Algorithm

In this paper, the application of modified genetic algorithms (MGA) in the optimization of the ARX Model-based observer of the Pneumatic Artificial Muscle (PAM) manipulator is investigated. The new MGA algorithm is proposed from the genetic algorithm with important additional strategies, and consequently yields a faster convergence and a more accurate search. Firstly, MGA-based identification method is used to identify the parameters of the nonlinear PAM manipulator described by an ARX model in the presence of white noise and this result will be validated by MGA and compared with the simple genetic algorithm (GA) and LMS (Least mean-squares) method. Secondly, the intrinsic features of the hysteresis as well as other nonlinear disturbances existing intuitively in the PAM system are estimated online by a Modified Recursive Least Square (MRLS) method in identification experiment. Finally, a highly efficient self-tuning control algorithm Minimum Variance Control (MVC) is taken for tracking the joint angle position trajectory of this PAM manipulator. Experiment results are included to demonstrate the excellent performance of the MGA algorithm in the NARX model-based MVC control system of the PAM system. These results can be applied to model, identify and control other highly nonlinear systems as well.

Parameter Estimation of Power System Signals Based on Cosine Self-Convolution Window With Desirable Side-Lobe Behaviors

Parameter estimation is an important topic in power system signal-processing tasks. A new class of windows, the cosine self-convolution window (CSCW), is proposed. The main-lobe and side-lobe behaviors of the first to the third order CSCWs are studied. A CSCW-based improved fast Fourier transform algorithm (FFT) for estimating power system signal parameters, such as frequency, phase, and amplitude, is given. The CSCW has a low peak side-lobe level, a high side-lobe decaying rate, and a simple spectral representation. Leakage errors and harmonic interferences are thus reduced considerably by weighting samples with the CSCW. The CSCW-based improved FFT algorithm can be easily implemented in embedded systems. The effectiveness of the proposed method was analyzed by means of computer simulations and practical experiments for multifrequency signals with the variations of the power system frequency as well as the presence of white noise and interhamonics.

Application of DOA Estimation Algorithms in Smart Antennas Systems

Concept of wireless communication systems which use smart antennas is based on digital signal processing algorithms. Thus, the smart antennas systems become capable to locate and track signals by the both: users and interferers and dynamically adapts the antenna pattern to enhance the reception in Signal-Of-Interest direction and minimizing interference in Signal-Of-Not-Interest direction. Hence, Space Division Multiple Access system, which uses smart antennas, is being used more often in wireless communications, because it shows improvement in channel capacity and co-channel interference. However, performance of smart antenna system greatly depends on efficiency of digital signal processing algorithms. The algorithm uses the Direction of Arrival (DOA) algorithms to estimate the number of incidents plane waves on the antenna array and their angle of incidence. This paper investigates performance of the DOA algorithms like MUSIC, ESPRIT and ROOT MUSIC on the uniform linear array in the presence of white noise. The simulation results show that MUSIC algorithm is the best. The resolution of the DOA techniques improves as number of snapshots, number of array elements and signal-to-noise ratio increases.

Determination of gravity anomaly at sea level from inversion of satellite gravity gradiometric data

Gravity gradients can be used to determine the local gravity field of the Earth. This paper investigates downward continuation of all elements of the disturbing gravitational tensor at satellite level using the second-order partial derivatives of the extended Stokes formula in the local-north oriented frame to determine the gravity anomaly at sea level. It considers the inversion of each gradient separately as well as their joint inversion. Numerical studies show that the gradients T zz , T xx , T yy and T xz have similar capability of being continued downward to sea level in the presence of white noise, while the gradient T yz is considerably worse than the others. The bias-corrected joint inversion process shows the possibility of recovering the gravity anomaly with 1 mGal accuracy. Variance component estimation is also tested to update the observation weights in the joint inversion.

M-FSK Carrier Gain Adjustment for Improved Power-Line Communications

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> This paper describes carrier gain adjustment (CGA) in the CENELEC <formula formulatype="inline"><tex Notation="TeX">$A$</tex></formula>-band, a counter-measure against the negative impact of a transmitter coupling circuit's filter characteristic in this band. As the CENELEC <formula formulatype="inline"><tex Notation="TeX">$A$</tex> </formula>-band lies very close to the power waveform frequency, a steep <formula formulatype="inline"><tex Notation="TeX">$-$</tex></formula>40 dB/decade coupler filtering slope is present in the lower parts of this band. Therefore, different symbol carriers (of different frequencies) are exposed to different attenuation factors. With linear amplification, only the least attenuated carrier can be amplified to the maximum level allowed by regulations, whilst the other carriers will be transmitted below the maximum level. Conversely, all carriers are exposed to similar noise levels, present on the power-line. CGA however, counters the unequal attenuation effect of the transmitter coupling circuit, by amplifying all carriers to an equal, maximum amplitude. As carrier gain adjustment is directly linked to the frequency response of the transmitter coupling circuit, this coupler needs to be characterized before implementing CGA. As measuring rod for this study, the performance of orthogonal M-ary frequency shift keying without coding, in the presence of white noise, is used. Results show that under the above conditions, carrier gain adjustment proves successful in equalizing the attenuating effect of the transmitter coupling circuit, thereby improving overall performance. </para>

Infants’ ability to recognize speech in the presence of amplitude-modulated background noise.

Adults experience a release of masking when the amplitude level of a masker varies [Festen and Plomp (1990) and Wilson and Carhart (1969)], especially when the variation occurs in a slow, predictable manner [Gustafsson and Arlinger (1994)]. This pattern of performance has been described as “listening in the dips” of the signal and is a form of selective attention: focusing one’s attention on those time periods of the signal that are likely to be most beneficial. Infants have poor selective attention abilities for different frequency regions [Bargones and Werner (1994)]; if they similarly are less able to attend to particular points in time, they should show no advantage when the amplitude level of a masker varies. We presented infants with either their own name or a foil name in the presence of white noise; the noise was either constant in amplitude or varied at a 10-Hz modulation at a depth of 12 dB. Infants showed a disadvantage when faced with amplitude-modulated background noise (that is, they showed stronger recognition of their name when the noise had a constant amplitude than a varying amplitude), suggesting that the modulation itself may have attracted attention away from the target speech. [Work supported by NSF BCS0642294.]

Application of the maximum entropy method in ultrasound nondestructive testing for scatterer imaging with allowance for multiple scattering

The possibility of solving the inverse scattering problem with allowance for the effect of multiple scattering between the scatterers by the least-squares method that minimizes the solution’s residual is considered. Since the problem is ill-posed, Tikhonov’s regularization is efficient with the entropy of the estimate of the measured field taken as the stabilizing functional, which is the essence of the maximum entropy method. The method is implemented in its multifrequency version. Results of the application of the maximum entropy method in numerical experiments are provided with images reconstructed in different frequency ranges in the presence of white noise.

Complementary responses to mean and variance modulations in the perfect integrate-and-fire model

In the perfect integrate-and-fire model (PIF), the membrane voltage is proportional to the integral of the input current since the time of the previous spike. It has been shown that the firing rate within a noise free ensemble of PIF neurons responds instantaneously to dynamic changes in the input current, whereas in the presence of white noise, model neurons preferentially pass low frequency modulations of the mean current. Here, we prove that when the input variance is perturbed while holding the mean current constant, the PIF responds preferentially to high frequency modulations. Moreover, the linear filters for mean and variance modulations are complementary, adding exactly to one. Since changes in the rate of Poisson distributed inputs lead to proportional changes in the mean and variance, these results imply that an ensemble of PIF neurons transmits a perfect replica of the time-varying input rate for Poisson distributed input. A more general argument shows that this property holds for any signal leading to proportional changes in the mean and variance of the input current.

Beam-forming and matched filter techniques for the underwater acoustic detection of UHE neutrino

The search for UHE neutrinos is one of the most promising fields in astroparticle physics. The experimental techniques proposed to identify cosmic neutrino signatures are mainly three: the detection of Cherenkov blue light originated by charged leptons (electrons, positrons, muons and tauons) from neutrino interaction in water or ice; the detection of acoustic waves produced by neutrino energy deposition in water, ice or salt; the detection of radio pulses following neutrino interaction in ice or salt. Due to the expected neutrino fluxes (≈10 −8 E 2 Gev/cm 2 s sr) and due to their extremely low interaction cross-section (≈10 −32 cm 2 at 10 20 eV), huge target volumes (≈km 3) are required to detect them. Acoustic detection of neutrino is a very suitable technique since the sound attenuation length, at the frequency of interest, is of the order of km. Due to the small amplitude of the expected neutrino bipolar signal (≈10 mPa), it is mandatory to develop an effective algorithm that increases the signal to noise ratio (SNR). In the present work a combination of matched filter, applied to each single hydrophone, and a beam-forming technique applied to a small array of hydrophones is proposed. The matched filter is a well-known technique of signal processing that maximizes the SNR in the presence of white noise. Beam forming is a signal-processing technique used in sensor arrays for directional analysis; the signals from different sensors are combined in such a way that pressure waves arriving from a specific direction are coherently summed. Preliminary results on simulated data will be shown.

Combined use of correlation dimension and entropy as discriminating measures for time series analysis

We show that the combined use of correlation dimension (D2) and correlation entropy (K2) as discriminating measures can extract a more accurate information regarding the different types of noise present in a time series data. For this, we make use of an algorithmic approach for computing D2 and K2 proposed by us recently [Harikrishnan KP, Misra R, Ambika G, Kembhavi AK. Physica D 2006;215:137; Harikrishnan KP, Ambika G, Misra R. Mod Phys Lett B 2007;21:129; Harikrishnan KP, Misra R, Ambika G. Pramana – J Phys, in press], which is a modification of the standard Grassberger–Proccacia scheme. While the presence of white noise can be easily identified by computing D2 of data and surrogates, K2 is a better discriminating measure to detect colored noise in the data. Analysis of time series from a real world system involving both white and colored noise is presented as evidence. To our knowledge, this is the first time that such a combined analysis is undertaken on a real world data.

Continuous-time model identification of fractional order models with time delays

This paper deals with the continuous-time model identification (CMI) of fractional order systems with time delays. In this paper, a new linear filter is introduced for simultaneous estimation of all model parameters for commensurate fractional order systems with time delays (CFOTDS) based on step response data. The proposed method simultaneously estimates the time delay along with other model parameters in an iterative manner by solving simple linear regression equations. For the case when the fractional order is unknown, we also propose a nested loop optimization method where the time delay along with other model parameters are estimated iteratively in the inner loop and the fractional order is estimated in the non-linear outer loop. The applicability of the developed procedure is demonstrated on two fractal systems by doing Monte Carlo simulation analysis in the presence of white noise.

Perfect and almost perfect pulse compression codes for range spread radar targets

It is well known that a matched filter gives the maximum possible output signal-to-noise ratio (SNR) when the input is a scattering signal from a point like radar target in the presence of white noise. However, a matched filter produces unwanted sidelobes that can mask vital information. Several researchers have presented various methods of dealing with this problem. They have employed different kinds of less optimal filters in terms of the output SNR from a point-like target than that of the matched filter. In this paper we present a method of designing codes, called perfect and almost perfect pulse compression codes, that do not create unwanted sidelobes when they are convolved with the corresponding matched filter. We present a method of deriving these types of codes from any binary phase radar codes that do not contain zeros in the frequency domain. Also, we introduce a heuristic algorithm that can be used to design almost perfect codes, which are more suitable for practical implementation in a radar system. The method is demonstrated by deriving some perfect and almost perfect pulse compression codes from some binary codes. A rigorous method of comparing the performance of almost perfect codes (truncated) with that of perfect codes is presented.

Self-tuning control based on generalized minimum variance criterion for auto-regressive models

Theoretical problems on self-tuning control include stability, performance and convergence of the recursive algorithm involved. In this paper, the problem of controlling minimum or non-minimum phase auto-regressive models with constant but unknown parameters is considered. The stability of an algorithm obtained by combining a recursive estimator for the controller parameters and a generalized minimum variance criterion is proved. The main result is the theorem which assures the overall stability for the closed-loop system in presence of white noise in the input–output relation, where the estimated parameters do not necessarily converge to the true values. The algorithm is proved by the Lyapunov theory.

Robust Fundamental Frequency Estimation Combining Contrast Enhancement and Feature Unbiasing

A high-performance fundamental frequency estimator inspired by the human auditory system is presented. It uses a cubic-root transform and contrast enhancement on the spectral domain to enhance weak harmonics and suppress noise. The proposed weighted unbiasing process reduces multiple or submultiple pitch errors efficiently. Evaluation is performed under the presence of white noise, babble noise, and telephone channel distortion. The results show that the proposed method performs equivalent to or better than previous state-of-the-art methods in the majority of the noise and channel conditions.

The Suppression of Four-Wave Mixing by Random Dispersion

Pairwise interactions of optical pulses lead to the creation of four-wave mixing (FWM) products in the presence of periodic damping and amplification. In this manuscript, we examine how these FWM products grow in the presence of small to moderate random dispersion. Namely, we show that (i) the growth of the FWM products in the presence of white noise is inversely proportional to the noise strength $\bar{D}$, confirmed by both analytical and numerical results; (ii) the FWM products as a function of $\bar{D}$ obey a gamma-type probability distribution function; and (iii) the presence of either white or Ornstein–Uhlenbeck (OU) noise has a similar influence on the growth of these FWM products. This work shows that small random dispersion can effectively mitigate the deleterious effects of FWM in wavelength-division–multiplexed optical communications systems for either sech-type or Gaussian-type input pulses.

Enhanced ITER resistive wall mode feedback performance using optimal control techniques

In order to achieve the highest plasma pressure limits in ITER, resistive wall kink mode stabilization is required. A novel resistive wall mode linear observer and feedback controller designed using model reduction and optimal control theory and employing only proportional gain are described here that allow operation of ITER up to Cβ = 86% of the ideal wall limit using the present design external control coils. The full VALEN finite element ITER model containing ∼3000 modes was reduced to a minimum of 8 modes making real-time controller implementation possible. We find an order of magnitude reduction of the required control coil current and voltage in the presence of white noise from the no-wall limit to the optimal feedback system performance limit as compared with a traditional, classical controller.

Scaling and rotation invariant analysis approach to object recognition based on Radon and Fourier–Mellin transforms

Various types of orthogonal moments have been widely used for object recognition and classification. However, these moments do not natively possess scaling invariance, essential image normalization and binarization prior to moments extraction will lead to error of resampling and requantifying. This paper describes a new scaling and rotation invariant analysis method for object recognition. In the proposed method, the Radon transform is utilized to project the image onto projection space to convert the rotation of the original image to a translation of the projection in the angle variable and the scaling of the original image to a scaling of the projection in the spatial variable together with an amplitude scaling of the projection, and then the Fourier–Mellin transform is applied to the result to convert the translation in the angle variable and the scaling in the spatial variable as well as the amplitude scaling of the projection to a phase shift and an amplitude scaling, respectively. In order to achieve a set of completely invariant descriptors, a rotation and scaling invariant function is constructed. A k -nearest neighbors’ classifier is employed to implement classification. Theoretical and experimental results show the high classification accuracy of this approach as a result of using the rotation and scaling invariant function instead of image binarization and normalization, it is also shown that this method is relatively robust in the presence of white noise.

Nonlinear Estimation of Harmonic Signals

A nonlinear harmonic estimator (NHE) is proposed for extracting a harmonic signal and its fundamental frequency in the presence of white noise. This estimator is derived by applying an extended complex Kalman filter (ECKF) to a multiple sinusoidal model with state-representation and then efficiently specializing it for the case of harmonic estimation. The effectiveness of the NHE is verified using computer simulations.

Neurotoxicity of BFM-95 on the Medial Olivocochlear Bundle Assessed by Means of Contralateral Suppression of 2f1-f2 Distortion Product Otoacoustic Emissions

Berlin-Frankfurt-Munster 95 (BFM-95) is a common chemotherapeutic protocol against acute lymphoblastic leukemia (ALL). This prospective study investigates whether this protocol has an adverse effect on the medial olivocochlear bundle (MOCB) and/or outer hair cells' (OHCs) function. The distortion product otoacoustic emissions (DPOAEs) and their suppression by means of contralateral application of white noise were used for assessing the function of OHCs and the MOCB, respectively. Prospective study. Oncology and otorhinolaryngology departments in a pediatric hospital. Thirty-six children treated with ALL-BFM-95. Before chemotherapy, a baseline audiologic evaluation with tympanogram, standard and extended high frequency, pure-tone audiometry, and DPOAEs in the absence and presence of white noise was performed in all children. This population was divided in three groups. In a first group (n = 12), the evaluation was repeated after four sessions of vincristine administration; in the second group (n = 12), after 8 sessions; and in the third group (n = 12), several months after completion of the protocol. DPOAEs suppression by contralateral application of white noise. In the first and the third groups, we observed no changes in DPOAE amplitudes. Nevertheless, in the second group, the DPOAEs demonstrated significant decrease at 1416, 1685, 2002, and 2380 Hz. At baseline examination, all groups presented significant suppression at all frequencies. After eight vincristine sessions, instead of suppression, an increase of amplitudes was noted at 5 of 12 frequencies. Efferent-mediated DPOAE suppression reappeared in the third group at all frequencies (significant at 5 of 12 frequencies). ALL-BFM-95 seems to exert an early and reversible toxic effect on the MOCB, whereas its effects on OHCs are minimal and reversible. These minimal cochleotoxic and neurotoxic properties of ALL-BFM-95 might prove useful for research studies on the role of efferent innervation in hearing.

Temporal Behavior of the Conditional and Gibbs’ Entropies

We study the temporal approach to equilibrium of the Gibbs’ and conditional entropies for stochastic systems in the presence of white noise. The conditional entropy will either remain constant or monotonically increase to its maximum of zero. However, the Gibbs’ entropy may have a variety of patterns of approach to its final value ranging from a monotone increase or decrease to an oscillatory approach. We have illustrated all of these behaviors using examples in which both entropy dynamics can be determined analytically.