Noise Considerations Research Articles

Feature selection based on MBFOA for audio signal classification under consideration of Gaussian white noise

Audio classification is a difficult task because of the issue of extracting and choosing the optimum audio features. To reduce the computational complication from existing methods, this study proposes a feature-selection method based on modified bacterial foraging optimisation algorithm (MBFOA) for classification of audio signals. Enhanced mel-frequency cepstral coefficient and enhanced power normalised cepstral coefficients with peak and pitch are estimated the signal feature and optimised using MBFOA with the fitness function. Using the probabilistic neural network, the audio signal is classified into music and speech signal. Then, if the signal is music, the signal is classified as cello, clarinet, flute etc. If the signal is detected as a speech, then it is again classified as male or female voice. This approach shows that it is possible to boost the classification accuracy by using different features and optimisation technique.

Coordinated Beamforming for Downlink Visible Light Communication Networks

Visible light communication (VLC) is an emerging short-range optical wireless communication technology that is driven by the widespread deployment of light-emitting diodes (LEDs). Indoor VLC users may experience noticeable interference when independent transmitters utilizing wide-beam luminaires are closely located. In this paper, a coordinated beamforming (CB) scheme is proposed for downlink interference mitigation among the coexisting VLC attocells utilizing multi-luminaire transmitters. Compared to joint transmission (JT) schemes, wherein the data and channel state information are shared among transmitters of different attocells, the proposed CB scheme places lower requirements on the network in terms of backbone traffic, and is easier to implement in a practical deployment, though at the cost of compromised performance. In this paper, we investigate the downlink transmission of coordinated VLC attocells and focus on its transmitter design. The weighted sum mean square error (WSMSE) is adopted as the performance metric to take into consideration interference, noise, and fairness among users in system optimization. The WSMSE minimization problem is considered with linear beamforming restricted by amplitude constraints. Such constraints arise from the dynamic range limitations in typical LEDs. Moreover, we extend our design method to take into account possible mismatches in channel information available to the transmitters. Numerical examples are provided to illustrate the performance of the proposed CB scheme in typical VLC scenarios. We also quantify the performance gap among several coordination schemes including JT and CB.

Position Estimation and Compensation Based on a Two-Step Extended Sliding-Mode Observer for a MSFESS.

This paper aims to deal with the problem of rotor position estimation and compensation for a magnetically suspended flywheel energy storage system under the consideration of measurement noise and unknown disturbances. First, the flywheel system working principle and description are analyzed and, based on this, the mathematical model as well as the coordinates transformation are introduced. For the purpose of the state estimation, a two-step extended sliding-mode observer is considered to obtain the estimates of the rotor angular position. In this control strategy, a traditional sliding-mode observer is adopted as a first-step original state estimator. After that, the relationship between the angular position and the estimation error is established and a second-step observer is designed to obtain the estimation of the error. The estimated error is then used to compensate the real values of the rotor angular position generated by the first-step observer. To reject the influences of the measurement noise and unknown disturbances, the H∞ optimization strategy is considered to determine the second-step observer structure. Finally, experimental results are presented to demonstrate the effectiveness of the proposed method. It is demonstrated that the proposed two-step observer method has a better estimation accuracy and control performance.

Influence of sample surface height for evaluation of peak extraction algorithms in confocal microscopy.

The axial resolution of confocal microscopy is not only dependent on optical characteristics but also on the utilized peak extraction algorithms. In previous evaluations of peak extraction algorithms, sample surface height is generally assumed to be zero, and only sampling-noise-induced peak extraction uncertainty was analyzed. Here we propose a sample surface-height-dependent (SHD) evaluation model that takes the combined considerations of sample surface height and noise for comparisons of algorithms' performances. Monte Carlo simulations were first conducted on the centroid algorithm and several nonlinear fitting algorithms such as the parabola fitting algorithm, Gaussian fitting algorithm, and sinc2 fitting algorithm. Subsequently, the evaluation indicators, including mean peak extraction error and mean uncertainty were suggested for the algorithms' performance ranking. Finally, experimental verifications of the SHD model were carried out using a fiber-based chromatic confocal system. From our simulations and experiments, we demonstrate that sample surface height is a critical influencing factor in peak extraction computation in terms of both the accuracy and standard deviations. Compared to the conventional standard uncertainty evaluation model, our SHD model can provide a more comprehensive characterization of peak extraction algorithms' performance and offer a more flexible and consistent reference for algorithm selection.

A framework for annotating OpenStreetMap objects using geo-tagged tweets

Recent years have witnessed an explosion of geospatial data, especially in the form of Volunteered Geographic Information (VGI). As a prominent example, OpenStreetMap (OSM) creates a free editable map of the world from a large number of contributors. On the other hand, social media platforms such as Twitter or Instagram supply dynamic social feeds at population level. As much of such data is geo-tagged, there is a high potential on integrating social media with OSM to enrich OSM with semantic annotations, which will complement existing objective description oriented annotations to provide a broader range of annotations. In this paper, we propose a comprehensive framework on integrating social media data and VGI data to derive knowledge about geographical objects, specifically, top relevant annotations from tweets for objects in OSM. We first integrate geo-tagged tweets with OSM data with scalable spatial queries running on MapReduce. We propose a frequency based method for annotating boundary based geographic objects (a polygon), and a probability based method for annotating point based geographic objects (Latitude and Longitude), with consideration of noise. We evaluate our methods using a large geo-tagged tweets corpus and representative geographic objects from OSM, which demonstrates promising results through ground-truth comparison and case studies. We are able to produce up to 80% correct names for geographical objects and discover implicitly relevant information, such as popular exhibitions of a museum, the nicknames or visitors’ impression to a tourism attraction.

Robust active guidance control using the µ-synthesis method for a tramcar with independently rotating wheelsets

This paper presents a robust active guidance controller that uses the µ-synthesis method to improve the ability of guidance and to reduce the wheel–rail wear under the consideration of system nonlinearity, parameter uncertainty, and measurement noise in tramcars with independently rotating wheelsets (IRWs). Each wheel of the tramcar is connected to a sider motor, and the active yaw moment is generated by the torque differences between the left and right wheels in the same axle. To achieve local control, the wheel–rail force and the primary suspension force are considered as external disturbances, and the IRW state–space model is modeled independent of the tramcar system. The effectiveness of the controller is mainly verified by the cosimulation method: the dynamic model of the tramcar is established in SIMPACK, and the controller model is established in MATLAB. The simulation results show that compared with the passive case, for the actual tramcar, the control method can improve the vehicle's running performance and can significantly reduce the wheel–rail wear in both straight and curved tracks. A 1:5 scaled tramcar model is used for the active guidance experiment to further verify the effectiveness of the algorithm.

Noise Limits in Thin-Film Magnetoelectric Sensors With Magnetic Frequency Conversion

To enable the measurement of low-frequency magnetic signals with cantilever type thin-film magnetoelectric sensors, magnetic frequency conversion transfers the frequency of the desired signal into the mechanical resonance of the cantilever. The system electronics for the realization of this approach and the approach itself introduce additional noise sources as compared with direct detection, which lowers the limit of detection. In this paper, the magnetic frequency conversion noise sources are reviewed, discussed, and evaluated for our setup. The model for the nonlinear transfer process is implemented in the time domain. This enables the consideration of the pump noise in a noise equivalent circuit. For the sensor type under investigation, the dominant noise near its optimal working point originates from the pump source. If the noise of the pump can be decreased and magnetic excess noise is not dominant, the noise limit is the thermal-mechanical noise of the sensor. The implementation of a filter after the excitation source decreases the limit of detection to 60 pT/ $\sqrt {\text {Hz}}$ at 10 Hz.

Dynamic Coverage Control in a Time-Varying Environment Using Bayesian Prediction

This paper investigates the dynamic coverage control problem for a group of agents with unknown density function. A cost function, depending on a certain metric and the density function, is defined to describe the performance of coverage network. Since the optimal deployment of agents is closely depending on the density function, we employ the Bayesian prediction approaches to estimate the density function. Moreover, a novel coverage-control-customized algorithm is proposed to acquire the Bayesian parameters. The merits of this Bayesian-based spatial estimation algorithm are the consideration of measurement noise and the capability of dealing time-varying density function. However, the estimated density function from Bayesian framework follows normal distribution, which leads the cost function to a stochastic process. To deal with this type of cost function, a discrete control scheme is proposed to steer the agents approaching to a near-optimal deployment. The mean-square stability of the proposed coverage system is further analyzed. Finally, numerical simulations are provided to verify the effectiveness of the proposed approaches.

Quantitative interpretation sensitivity to angle and frequency-dependent pre-stack time shift, amplitude and phase perturbations

As discussed by Long (2017), marine ‘broadband’ signal processing flows typically incorporate a combination of free-surface deghosting, spectral shaping, and attenuation compensation. Overall, there are many opportunities to corrupt the phase content in an angle-dependent and frequency-dependent manner during any signal processing flow, and such risks may increase during aggressive ‘broadband’ flows. We conducted a synthetic modelling study to quantify and understand how angle-dependent time shifts, angle-dependent frequency variations, or frequency-dependent phase errors can impact the recovery of elastic impedance attributes using pre-stack simultaneous seismic inversion. All modelling and inversion was 2D in nature, included no noise considerations, and assumed the velocity model was perfectly understood.

Impact of gasoline and Diesel blends on combustion noise and pollutant emissions in Premixed Charge Compression Ignition engines

Research efforts in the automotive sector focus on developing new combustion concepts for mitigating the emissions of nitrous oxides and soot of conventional Diesel combustion. One of the most promising concept is the Premixed Charge Compression Ignition. In this, the fuel burns in premixed conditions, avoiding the formation of soot whereas nitrous oxides are controlled using large amounts of exhaust gas recirculation. Because of the premixed combustion, high fuel-burning velocities are produced, whence combustion noise is deteriorated. In order to mitigate this drawback, different blends of gasoline and Diesel fuels are being considered due to their suitability for this combustion characteristics. The effect of these fuel blends on emissions, performance and engine noise is analysed in this paper with the aim to provide additional knowledge of the fundamental issues of this particular combustion mode. The study also includes sweeps of both the start of injection and the amount of exhaust gas recirculation, in order to evaluate further degrees of freedom in the optimisation of the engine settings. Results show that the consideration of the engine noise together with both performance and emissions, reduces dramatically the margin of variation of the combustion settings, limiting therefore the operation range of the engine.

7-2 光沢制御のためのノイズを考慮した鏡面反射の分離(第7部門[テーマ講演]質感知覚と映像表現・メディア処理)

7-2 光沢制御のためのノイズを考慮した鏡面反射の分離(第7部門[テーマ講演]質感知覚と映像表現・メディア処理)

Demodulation Techniques for Self-Oscillating Eddy-Current Displacement Sensor Interfaces: A Review

This paper presents a comprehensive study of demodulation techniques for high-frequency self-oscillating eddy-current displacement sensor (ECDS) interfaces. Increasing the excitation frequency is essential for lowering the skin depth in many demanding industrial applications, that require better resolution. However, a high excitation frequency poses design challenges in the readout electronics, and particularly in the demodulation functional block. We analyze noise, linearity, and stability design considerations in amplitude demodulators for nanometer and sub-nanometer ECDSs. A number of state-of-the-art amplitude demodulation techniques employed in high-frequency ECDSs are reviewed, and their pros and cons are evaluated.

A New Robust Tracking Control Design for Turbofan Engines: H∞/Leitmann Approach

In this paper, a H ∞ /Leitmann approach to the robust tracking control design is presented for an uncertain dynamic system. This new method is developed in the following two steps. Firstly, a tracking dynamic system with simultaneous consideration of parameter uncertainty and noise is modeled based on a linear system and a reference model. Accordingly, a “nominal system” from the tracking system is defined and controlled by a H ∞ control to obtain the asymptotical stability and noise resistance. Secondly, by making use of a Lyapunov function and the norm boundedness, a new robust control with the “Leitmann approach” is designed to cope with the uncertainty. The two controls collaborate with each other to achieve “uniform tracking boundedness” and “uniform ultimate tracking boundedness”. The new approach is then applied to an aircraft turbofan control design, and the numerical simulation results show the prescribed performances of the closed-loop system and the advantage of the developed approach.

Nearly optimal measurement schemes in a noisy Mach-Zehnder interferometer with coherent and squeezed vacuum

The use of an interferometer to perform an ultra-precise parameter estimation under noisy conditions is a challenging task. Here we discuss nearly optimal measurement schemes for a well known, sensitive input state, squeezed vacuum and coherent light. We find that a single mode intensity measurement, while the simplest and able to beat the shot-noise limit, is outperformed by other measurement schemes in the low-power regime. However, at high powers, intensity measurement is only outperformed by a small factor. Specifically, we confirm, that an optimal measurement choice under lossless conditions is the parity measurement. In addition, we also discuss the performance of several other common measurement schemes when considering photon loss, detector efficiency, phase drift, and thermal photon noise. We conclude that, with noise considerations, homodyne remains near optimal in both the low and high power regimes. Surprisingly, some of the remaining investigated measurement schemes, including the previous optimal parity measurement, do not remain even near optimal when noise is introduced.

Dynamic Characteristics of a Pressure-Compensated Inlet-Metered Pump

Pressure-compensated pumps are routinely used for supplying fluid power for hydraulic control systems. These pumps traditionally exhibit significant overshoot and oscillation before reaching a steady-state pressure condition, thus requiring the use of downstream safety valves to prevent over pressurization. In addition to over pressurizing the hydraulic control system, the response of the traditional pressure-compensated pump often induces excessive noise and creates instability for other components within the system. In this paper, a nontraditional pressure-compensated hydraulic pump is studied based upon the paradigm that has been offered by diesel-engine technology. This technology uses an inlet-metered pump to provide pressurized fuel for the high-pressure, fuel-injector rail. The analysis of this paper shows that a system of this type may be used to produce a first-order pressure response with no overshoot and oscillation, and that the characteristic time constant and settling time may be designed by specifying parameters that are identified in this research. The problem of cavitation damage is also discussed based upon preliminary testing done at the University of Missouri, and it is suggested that by using hardened machine parts cavitation damage may be prevented in these machines. In conclusion, this paper shows that continued development of the inlet-metered pump may be warranted for those applications where pressure overshoot and oscillation cannot be tolerated due to safety, noise, or other dynamical considerations.

Efficient spatial coverage by a robot swarm based on an ant foraging model and the Lévy distribution

This work proposes a control law for efficient area coverage and pop-up threat detection by a robot swarm inspired by the dynamical behavior of ant colonies foraging for food. In the first part, performance metrics that evaluate area coverage in terms of characteristics such as rate, completeness and frequency of coverage are developed. Next, the Keller–Segel model for chemotaxis is adapted to develop a virtual-pheromone-based method of area coverage. Sensitivity analyses with respect to the model parameters such as rate of pheromone diffusion, rate of pheromone evaporation, and white noise intensity then identify and establish noise intensity as the most influential parameter in the context of efficient area coverage and establish trends between these different parameters which can be generalized to other pheromone-based systems. In addition, the analyses yield optimal values for the model parameters with respect to the proposed performance metrics. A finite resolution of model parameter values were tested to determine the optimal one. In the second part of the work, the control framework is expanded to investigate the efficacy of non-Brownian search strategies characterized by Levy flight, a non-Brownian stochastic process which takes variable path lengths from a power-law distribution. It is shown that a control law that incorporates a combination of gradient following and Levy flight provides superior area coverage and pop-up threat detection by the swarm. The results highlight both the potential benefits of robot swarm design inspired by social insect behavior as well as the interesting possibilities suggested by considerations of non-Brownian noise.

State observation–based control algorithm for dynamic vibration absorbing systems featuring magnetorheological elastomers: Principle and analysis

Based on state observation, a rapid, stable, and effective control algorithm for magnetorheological elastomer (MRE)–based dynamic vibration absorbers (DVAs) applied to automobile powertrain mount systems is proposed and investigated in this article. The state-space model for powertrain mount systems with MRE-based DVAs is established using the rank criterion method for observable systems. According to the principle of system reconfiguration, a full state observation model using an adaptive Kalman filter with Sage–Husa noise estimator is developed. With the state vectors estimated by the Kalman filter, the phase difference between the displacement of the dynamic mass of the MRE-based DVA relative to the powertrain and the absolute displacement of the powertrain is updated continuously based on Simpson’s rule. By adjusting the applied current to the MRE-based DVA with fuzzy logic control corresponding to the cosine value of the phase difference, the natural frequency of the MRE-based DVA could track the excitation frequency of the powertrain well, which results in vibration attenuation of the powertrain mount system. With consideration of excitation noise, time delays, and parametric uncertainties, the simulation experiments of vibration attenuation performance of the MRE-based DVA for the powertrain mount systems when under time-varying excitation are carried out to verify the effectiveness and the stability of the proposed algorithm with fuzzy steps. The simulation results show that when using the proposed algorithm with fuzzy steps, the MRE-based DVA could attenuate the powertrain vibration rapidly and effectively, and the vibration attenuation performance will not be influenced by noise, time delays, and parametric uncertainties.

Combustion and Engine-Core Noise

The implementation of advanced low-emission aircraft engine technologies and the reduction of noise from airframe, fan, and jet exhaust have made noise contributions from an engine core increasingly important. Therefore, meeting future ambitious noise-reduction goals requires the consideration of engine-core noise. This article reviews progress on the fundamental understanding, experimental analysis, and modeling of engine-core noise; addresses limitations of current techniques; and identifies opportunities for future research. After identifying core-noise contributions from the combustor, turbomachinery, nozzles, and jet exhaust, they are examined in detail. Contributions from direct combustion noise, originating from unsteady combustion, and indirect combustion noise, resulting from the interaction of flow-field perturbations with mean-flow variations in turbine stages and nozzles, are analyzed. A new indirect noise-source contribution arising from mixture inhomogeneities is identified by extending the theory. Although typically omitted in core-noise analysis, the impact of mean-flow variations and nozzle-upstream perturbations on the jet-noise modulation is examined, providing potential avenues for future core-noise mitigation.

Design and Analysis of CMOS Low-Phase-Noise Low-Jitter Subharmonically Injection-Locked VCO With FLL Self-Alignment Technique

Design and analysis of low-phase-noise low-jitter subharmonically injection-locked voltage-controlled oscillator (VCO) with frequency-locked loop (FLL) self-alignment technique is presented in this paper using 90-nm CMOS process. The issue of the narrow locking range for the subharmonically injection-locked VCO (SILVCO) can be resolved over the variations, especially for high subharmonic number and millimeter-wave band, since the control voltage is adaptively adjusted using the proposed innovative method to refer to the subharmonic input frequency. A theoretical model of the SILVCO with FLL self-alignment technique is addressed for the design consideration and phase noise evaluation. With a subharmonic number of 16, the operation frequency of the proposed $K$ -band circuit is from 24 to 26.1 GHz. The measured minimum phase noise at 1-MHz offset and jitter integrated from 1 kHz to 40 MHz are −114.3 dBc/Hz and 56.6 fs, respectively. As the temperature is from 20 °C to 70 °C, the measured deviations of output power, phase noise, and jitter are within 2 dB, 3 dB, and 67 fs, respectively. This paper demonstrates excellent performance and good robustness, and it can be compared with the previously reported state-of-the-art clock generators in silicon-based technologies.

Preface

Stochasticity, sometimes referred to as noise, is unavoidable in biological systems. Noise, which exists at all biological scales ranging from gene expressions to ecosystems, can be detrimental or sometimes beneficial by performing unexpected tasks to improve biological functions. Often, the complexity of biological systems is a consequence of dealing with uncertainty and noise, and thus, consideration of noise is necessary in mathematical models. Recent advancement of technology allows experimental measurement on stochastic effects, showing multifaceted and perplexed roles of noise. As interrogating internal or external noise becomes possible experimentally, new models and mathematical theory are needed. Over the past few decades, stochastic analysis and the theory of nonautonomous and random dynamical systems have started to show their strong promise and relevance in studying complex biological systems. This special issue represents a collection of recent advances in this emerging research area.For more information please click the “Full Text” above.