Noise Measurement

We consider the problem of learning a coefficient vector x 0 ∈ R N from noisy linear observation y = Ax 0 + w ∈ R n . In many contexts (ranging from model selection to image processing) it is desirable to construct a sparse estimator x. In this case, a popular approach consists in solving an ℓ 1 -penalized least squares problem known as the LASSO or Basis Pursuit DeNoising (BPDN).

A complete analysis of low-noise 0.1 m gate AlInAs/GaInAs HEMT's has been performed by using a semiclassical Monte Carlo simulation. The validity of the model has been checked through the comparison of the simulated results with static, dynamic and noise experimental measurements of real HEMTs. In order to reproduce the experimental results, we have included in the model some important real effects such as degeneracy, surface charges, T-shape of the gate, presence of dielectrics and contact resistances. Moreover, the extrinsic parameters of the devices have been added to the usual intrinsic small-signal equivalent circuit, thus allowing the calculation of the real noise of the HEMTs (characterized using the extrinsic minimum noise . In this way, we make possible not only the comparison with the experimental noise results, but also the analysis of the influence of the parasitic elements, the device width or the number of gate fingers on the noise of the HEMTs. The reliability of the simulator allows us to realize "computer experiments" which will make faster and cheaper the optimization process of the device design. for his work on the modeling and the characterization of MES-FETs and HEMTs. In 1977, he joined the Centre Hyperfrequences et Semiconducteurs, University of Lille, France. He is now Professor of electronics at the University of Lille. His main research interests are concerned with the modeling, the realization and the characterization of low noise devices for application in the centimeter and millimeter wave ranges.

This correspondence describes a method for estimating the parameters of an autoregressive (AR) process from a finite number of noisy measurements. The method uses a modified set of Yule-Walker (YW) equations that lead to a quadratic eigenvalue problem that, when solved, gives estimates of the AR parameters and the measurement noise variance.

A growing interest for techniques and systems allowing the early detection and monitoring of damage based on vibration analysis is clearly present in different research and application areas, such as civil constructions, mechanical systems, and aircraft and aerospace industry. However, an important element for the applicability of modal-based damage assessment techniques in practice is the automation of the identification and tracking procedure.

Most of the existing techniques for palmprint recognition rely on metrics, typically based on static functions, which evaluate the distance between a pair of features. In this paper, we propose a new technique for palmprint verification based on a dynamical system approach for principal palm lines matching. The proposed dynamic algorithm is recursive and involves a positive linear dynamical system, whose evolution depends on the matching level between the two input images. In a preprocessing phase, the procedure iteratively erodes both of the images to be compared, by eliminating points in each image that do not have enough close neighboring points both in the image itself and the comparison image. As a result of the iterations, only the points that have enough neighboring points in both the image itself and in the comparison image can survive. Thus, the output of the dynamical system converges either to zero, when a deep mismatch exists between the two images, or to a high value, when a good matching is observed. The results, in terms of verification, are in line with the state-of-the-art results in the current literature. The main advantage of the approach is its robustness when dealing with low-resolution and noisy images. The impact of noise (e.g., salt and pepper noise) is effectively reduced: images corrupted with such noise are easily recognized, while a randomly generated image is rejected even when compared with itself.

We propose a new hierarchical approach to resolution scalable lossless and near-lossless (NLS) compression. It combines the adaptability of DPCM schemes with new hierarchical oriented predictors to provide resolution scalability with better compression performances than the usual hierarchical interpolation predictor or the wavelet transform. Because the proposed hierarchical oriented prediction (HOP) is not really efficient on smooth images, we also

This review provides a comprehensive survey of noise research in MEMS. Some background on noise and on MEMS is provided. We review noise production mechanisms, and highlight work on the theory and modeling of noise in MEMS. Then noise measurements in the specific types of MEMS are reviewed. Inertial MEMS (accelerometers and angular rate sensors), pressure and acoustic sensors, optical MEMS, RF MEMS, surface acoustic wave devices, flow sensors, and chemical and biological MEMS, as well as data storage devices and magnetic MEMS, are reviewed. We indicate opportunities for additional experimental and computational research on noise in MEMS.

New advances in hot electron bolometer (HEB) mixers have recently resulted in record-low receiver noise temperatures at terahertz frequencies. We have developed quasi-optically coupled NbN HEB mixers and measured noise temperatures up to 2.24 THz, as described in this paper. We project the anticipated future performance of such receivers to have even lower noise temperature and local-oscillator power requirement as well as wider gain and noise bandwidths. We introduce a proposal for integrated focal plane arrays of HEB mixers that will further increase the detection speed of terahertz systems.

To improve interference robustness of wireless communication, spread spectrum techniques are often used. We use the chirp spreading technique along with FSK and PSK binary modulation schemes to obtain interference robust radio communication. The performance of chirped-FSK and chirped-PSK modulation through a white gaussian noise channel is simulated assuming a synchronized clock between transmitter and the receiver. We analyzed and simulated the error probability (BER) of the overall system in the presence of partial band of interference in the channel. The simulated BER is close to the estimated BER and they prove the superior performance of chirp-based modulation in the presence of interference.

This paper describes how an underwater vehicle can control its motion by sensing the surrounding flowfield and using the sensor measurements in a dynamic feedback controller. Limitations in existing sensing modalities for flowfield estimation are mitigated by using a fish-inspired distributed sensor array and a nonlinear observer. Estimation performance is further increased by optimizing sensor placement on the vehicle body. We optimize sensor placement along a streamlined body using measures of flowfield observability, namely the empirical observability gramian. Velocity potentials model the flow around the vehicle and a recursive Bayesian filter estimates the flow from noisy velocity measurements. To orient the body into the oncoming flow (a fish-inspired behavior known as rheotaxis) we implement a dynamic, linear controller that uses the estimated angle of attack. Numerical simulations illustrate the theoretical results.

We compute the zero frequency current noise numerically and in several limits analytically for the coulomb blockade problem consisting of two tunnel junctions connected in series. At low temperatures over a wide range of voltages, capacitances, and resistances it is shown that the noise measures the variance in the number of electrons in the region between the two tunnel junctions. The average current, on the other hand, only measures the mean number of electrons. Thus, the noise provides additional information about transport in these devices which is not available from measuring the current alone.

Online partial discharge (PD) detection still remains a very challenging task because of the strong electromagnetic interferences. In this paper, a new method of de-noising, using complex Daubechies wavelet (CDW) transform, has been proposed. It is a relatively recent enhancement to the real-valued wavelet transform because of two important properties, which are nearly shift invariant and availability of phase information. Those properties give CDW transform superiority over other real-valued wavelet transform. On the basis of CDW transform, complex threshold algorithm and combined information are devised. In order to take into account the difference of the real part and imaginary part of complex wavelet coefficients, complex threshold is devised to modify the real part and imaginary part respectively. Because the restored signal by inverse CDW transform is complex one, combined information is devised to combine the real part and imaginary part of complex signal to construct a real one, furthermore making full use of the simple information from complex signal.

The characteristics of tonal noise and the variations of flow structure around NACA0018 airfoil in a uniform flow are studied by means of simultaneous measurement of noise and velocity field by particle-image velocimetry to understand the generation mechanism of tonal noise. Measurements are made on the noise characteristics, the phase-averaged velocity field with respect to the noise signal, and the cross-correlation contour of velocity fluctuations and noise signal. These experimental results indicate that the tonal noise is generated from the periodic vortex structure on the pressure surface of the airfoil near the trailing edge of the airfoil. It is found that the vortex structure is highly correlated with the noise signal, which indicates the presence of noise-source distribution on the pressure surface. The vorticity distribution on the pressure surface breaks down near the trailing edge of the airfoil and forms a staggered vortex street in the wake of the airfoil.

The purpose of the present work is to investigate the potential of multi-frequency skin impedance as a versatile method for early detection of diabetes-related changes in the skin. The method implies application of a small sinusoidal voltage at various frequencies through the outermost layer of the skin. Skin impedance measurement is a quick and easy alternative to the expensive and slow study of skin biopsies by microscopy. However, the amount of data is overwhelming and the measurement noise is rather high and therefore multivariate data analysis is used. Different models of data transformation and data reduction for extraction of the parts of the data that correlate with patient status and other diagnostic parameters are discussed. Multivariate methods make it very easy to give a visual interpretation of the results. The results demonstrate how a regression model between skin impedance and other diagnostic data for diabetic patients and control groups can be developed into a novel diagnostic tool for the early discovery of possible complications for diabetic patients. q 1998 Elsevier Science B.V. All rights reserved.

This paper presents an application of Neural Networks to the control of a real system with measurement noise. The system is a kiln and the steps taken to arrive at direct and inverse models are described. The results of controlling the kiln with a Direct Inverse Control strategy are presented.

We present coherent phase modulation detection for laser phase noise measurements with delayed self-heterodyne method. The technique is demonstrated for the first time with the distributed feedback laser and external cavity laser. The results are within 15% of self-homodyne measurements using an optical coherent receiver.

Acoustical measures of vocal function are routinely used in the assessments of disordered voice, and for monitoring the patient's progress over the course of voice therapy. Typically, acoustic measures are extracted from sustained vowel stimuli where short-term and long-term perturbations in fundamental frequency and intensity, and the level of "glottal noise" are used to characterize the vocal function. However, acoustic measures extracted from continuous speech samples may well be required for accurate prediction of abnormal voice quality that is relevant to the client's "real world" experience. In contrast with sustained vowel research, there is relatively sparse literature on the effectiveness of acoustic measures extracted from continuous speech samples. This is partially due to the challenge of segmenting the speech signal into voiced, unvoiced, and silence periods before features can be extracted for vocal function characterization. In this paper we propose a joint time-frequency approach for classifying pathological voices using continuous speech signals that obviates the need for such segmentation. The speech signals were decomposed using an adaptive time-frequency transform algorithm, and several features such as the octave max, octave mean, energy ratio, length ratio, and frequency ratio were extracted from the decomposition parameters and analyzed using statistical pattern classification techniques. Experiments with a database consisting of continuous speech samples from 51 normal and 161 pathological talkers yielded a classification accuracy of 93.4%.

This work addresses the fundamental problem of distinguishing between a driver and passenger using a mobile phone, which is the critical input to enable numerous safety and interface enhancements. Our detection system leverages the existing car stereo infrastructure, in particular, the speakers and Bluetooth network. Our acoustic approach has the phone send a series of customized high frequency beeps via the car stereo. The beeps are spaced in time across the left, right, and if available, front and rear speakers. After sampling the beeps, we use a sequential change-point detection scheme to time their arrival, and then use a differential approach to estimate the phone's distance from the car's center. From these differences a passenger or driver classification can be made. To validate our approach, we experimented with two kinds of phones and in two different cars. We found that our customized beeps were imperceptible to most users, yet still playable and recordable in both cars. Our customized beeps were also robust to background sounds such as music and wind, and we found the signal processing did not require excessive computational resources. In spite of the cars' heavy multipath environment, our approach had a classification accuracy of over 90 percent, and around 95 percent with some calibrations. We also found, we have a low false positive rate, on the order of a few percent.

Structural vibration is the most significant source of structure-borne noise. Avoiding severe resonances of the structures in order to reduce noise generation is the main interest of engineering fields. This paper studied a typical example of the structure-borne noise reduction utilized in general engineering practices. Noise measurement and experimental modal analysis demonstrated that some resonance modes of the structure contribute highly to noise generation.

This paper focuses on the implementation of various diagnostics for optimizing chemical oxygen iodine laser. This paper also dwells on the measurement methodologies and instrumentation employed in these diagnostic systems. The prime diagnostics are for the measurement of vital species in form of iodine, singlet oxygen, and chlorine. Iodine concentration measurement (absorption at λ = 499 nm), chlorine utilization (absorption at λ = 330 nm), and singlet oxygen yield (emission at λ = 1.27 µm) have been implemented based on optical absorption/emission principle. Furthermore, online Mach number determination, which is critical for supersonic gas flows, laser pulse detection (at λ = 1315 nm), and flow rate measurement and control over wide range, have been carried out. A dedicated diagnostics and data acquisition system (DDAS) customized for parameter monitoring have been developed. The developed DDAS also serves the purpose of precise operation sequencing and parameter control. It is a 168-channel personal-computer-based system with customized interface electronics employing Visual C++ programming language with user-friendly graphical user interfaces. A detailed uncertainty analysis of various critical parameters has been also presented.

An acoustical environment survey was carried out in an air-conditioned oce building. A total of 52 rooms occupied by one or more workers were analysed. In this survey, we used questionnaires and physical noise measurements. The oces characteristics lead us to belive that the noise sources to be considered were only those inside each room; this means that when a room is occupied by only one person the noise of the air conditioning system prevails. Instead, when a room is occupied by more than one person, the noise generated by the oce activity prevails. Our results show that some noise indices are well correlated with subjective sensations of loudness and annoyance; we found the strongest correlation for the percentile level L A90 , and the equivalent sound pressure level. #

This paper presents a system approach to the residual echo suppression (RES) problem in a noisy acoustic environment. We propose a method that takes advantage of our existing robust acoustic echo cancellation system in order to obtain a residual echo estimate that closely resembles the true, noise-free residual echo. To achieve improved RES during strong near-end interference (e.g., double talk), a psychoacoustic postfilter is also used. The simulation results show that our RES based on the system approach outperforms a conventional estimation method. Comparing the postfiltered output to the unprocessed one indicates that our proposed RES approach can raise the PESQ score by more than half a point.

The aim of this paper is to propose diffusion strategies for distributed estimation over adaptive networks, assuming the presence of spatially correlated measurements distributed according to a Gaussian Markov random field (GMRF) model. The proposed methods incorporate prior information about the statistical dependency among observations, while at the same time processing data in real-time and in a fully decentralized manner. A detailed mean-square analysis is carried out in order to prove stability and evaluate the steady-state performance of the proposed strategies. Finally, we also illustrate how the proposed techniques can be easily extended in order to incorporate thresholding operators for sparsity recovery applications. Numerical results show the potential advantages of using such techniques for distributed learning in adaptive networks deployed over GMRF.

Spam and noisy ratings affect the performance of recommendation systems which can lead to incorrect estimations and predictions. The challenge is to discover noisy ratings early in order to isolate its impact. In this paper we suggest an analysis using positive feedback which considers the user's level of confidence, and grades the user from completely honest to complete dishonest. The calculated user's level of confidence is computed based upon the detected level of honesty and affect his ratings. Each domain of ontologies has a calculated region of rejection and non-rejection using each user confidence level, placing his ratings in one region or another and thereby affecting his level of confidence. We used a Movie Lens of 1M ratings dataset to perform the required training. Suggested method has distinguished perfectly between Normal, Excess, Inferiority, and completely dishonest.

We propose a novel technique allowing the use of the three-cornered-hat method with two devices under test (DUTs) and a time-tagging system that employs a common reference oscillator. The precision of a time-tagging system is reduced by fluctuations in the timebase, which are canceled when the relative phase between the two DUTs is measured. However, the raw timetags in this system provide a phase comparison between the DUTs and the system timebase, allowing the use of the three-cornered hat with some dual-channel measurement instruments.

In this paper an identification method to estimate the parameters of a first order plus time delay model is proposed. Such a method directly obtains these parameters using a new linear regression equation. No iterations in calculation are needed. A simple true/false criterion to establish if the hypothesis on the process type is correct can be easily derived. The proposed method shows an acceptable robustness to disturbance and measurement noise as it is confirmed by several simulated experiments.

A low noise constant current source used for measuring the 1/f noise in disordered systems in ohmic as well as non-ohmic regime is described. The source can supply low noise constant current starting from as low as 1 µA to a few tens of mA with a high voltage compliance limit of around 20 Volts. The constant current source has several stages which can work in a standalone manner or together to supply the desired value of load current. The noise contributed by the current source is very low in the entire current range. The fabrication of a low noise voltage preamplifier modified for bias dependent noise measurements and based on the existing design available in the MAT04 data sheet is also described.

Abstract. In this contribution we present experiments on color image enhancement for several dierent non-linear lters which originally were de ned for gray-level images. We disturb sample images by dierent types of noise and measure performance of the lters. We provide signal-to-noise measurements as well as perceived color dierence in E as dened by the CIE. All images and test programs are provided online on the internet so that experiments can be validated by arbitrary users on any image data.

This paper deals with the control and observation of an induction motor using sliding-mode technique. Our aim is to regulate the speed and the square of the rotor flux magnitude to specified references. Assuming that all the states are measured, sliding surfaces are proposed within a sliding-mode control framework. Then, the stator voltages are derived such that the sliding surfaces are asymptotically attractive. Since, in practice, the rotor fluxes are not usually measurable, a sliding-mode observer is derived to estimate the rotor fluxes. Furthermore, it is shown that our observer is robust against modeling uncertainties and measurement noise. To illustrate our purpose, we present experimental results for a 0.37-kW induction motor obtained on a digital-signal-processor-based system (TMS 320C31/40 MHz). The experimental results show that the proposed control system is robust against rotor resistance variations.

This paper presents noise characterization of a CMOS 0.6-µm image sensors system. The integrated readout circuit adaptability allows measuring the photocurrent magnitude of each pixel in charge integration mode or in transimpedance mode. In order to find the minimum detectable signal of this system and to identify the main dominant noise sources, an accurate noise analysis is performed under dark and illumination conditions. Noise measurement and simulation with Spectre present a good agreement with the values predicted by the proposed analytical equations.

This paper compares four observers (virtual sensors) of vehicle sideslip angle and lateral forces. The first is linear and uses a linear vehicle model. The remaining observers use an extended nonlinear model. The three nonlinear observers are: extended Luenberger observer, extended Kalman filter and sliding-mode observer. Modeling, model simplification, and observers are described, and an observability analysis is performed for the entire vehicle trajectory. The paper also deals with three different sets of sensors to see the impact of observers results. Comparison is first done by simulation on a valid vehicle simulator, and then observers are used on experimental data. Our study shows that observers are more accurate than simple models as regards unmeasurable variables such as sideslip angle and transversal forces. It also shows that speed of center of gravity is not an indispensable variable here.

Increasing the bandwidth without degrading the noise performance represents the main challenge in the design of transimpedance amplifiers. This paper presents a novel circuit topology for a transimpedance amplifier that allows obtaining an improved tradeoff between equivalent input noise and bandwidth with respect to the conventional approach. The effectiveness of the new topology has been demonstrated by designing and testing a prototype of a transimpedance amplifier based on the proposed topology.

Fusing out-of-sequence information is a problem of growing importance due to an increased reliance on networked sensors embedded in complicated network architectures. The problem of fusing out-of-sequence measurements (OOSM) has received some attention in literature; however, most practical fusion systems, owing to compatibility with legacy sensors and limited communication bandwidth, send track information instead of raw measurements to the fusion node. Delays introduced by the network can result in the reception of out-of-sequence tracks (OOST). This paper considers the problem of fusing out-ofsequence measurements in general, and proposes an optimal Bayesian solution involving a joint probability density of current and past target states, referred to as augmented states. By representing tracks using equivalent measurements, the relationship between OOSM and OOST-based fusion is shown. The special case of Gaussian statistics is also addressed.

A terrestrial laser scanner measures the distance to an object surface with a precision in the order of millimeters. The quality of the individual points in a point cloud, although directly affecting standard processing steps like point cloud registration and segmentation, is still not well understood. The quality of a scan point is influenced by four major factors: instrument mechanism, atmospheric conditions, object surface properties and scan geometry. In this paper, the influence of the scan geometry on the individual point precision or local measurement noise is considered. The local scan geometry depends on the distance and the orientation of the scanned surface, relative to the position of the scanner. The local scan geometry is parameterized by two main parameters, the range, i.e. the distance from the object to the scanner and the incidence angle, i.e. the angle between incoming laser beam and the local surface normal. In this paper, it is shown that by studying the influence of the local scan geometry on the signal to noise ratio, the dependence of the measurement noise on range and incidence angle can be successfully modeled if planar surfaces are observed. The implications of this model is demonstrated further by comparing two point clouds of a small room, obtained from two different scanner positions: a center position and a corner position. The influence of incidence angle on the noise level is quantified on scans of this room, and by moving the scanner by 2 m, it is reduced by 20%. The improvement of the standard deviation is significant, going from 3.23 to 2.55 mm. It is possible to optimize measurement setups in such a way that the measurement noise due to bad scanning geometry is minimized and therefore contribute to a more efficient acquisition of point clouds of better quality.

A new digital signal processing approach to shaping intersymbol interference (ISI) and static mismatch errors simultaneously in oversampled multi-level digital to analog converters (DAC) has recently been proposed. In this paper, a mathematical framework is established for analyzing ISI errors as well as comparing the ISI sensitivities of different mismatch shaping algorithms. The framework is used to analyze the fundamental problems of popularly used algorithms such as data-weighted-averaging (DWA) in the presence of nonlinear ISI: Large-signal even-order distortion and frequency modulated harmonics at low signal levels. The new ISI-shaping algorithm results in significant improvement over previous schemes including the modified Mismatch Shaper (MMS) which also addresses ISI error. The new ISI shaper, while increasing the digital complexity, practically eliminates the need for conventional ISI mitigation techniques such as time consuming, layout-critical, non-automated and process specific analog design methods. The advantages of ISI shaping is further verified on an experimental audio DAC with simple non-return-to-zero (NRZ) current steering segments implemented in a 45 nm CMOS process and running off a single-phase clock of only 3.072 MHz.

. As a consequence, there is a growing interest in efficient implementations of the AES. For many applications, these implementations need to be resistant against side channel attacks, that is, it should not be too easy to extract secret information from physical measurements on the device. This article presents the first results on the feasibility of power analysis attack against an AES hardware implementation. Our attack is targeted against an ASIC implementation of the AES developed by the ETH Zurich. We show how to build a reliable measurement setup and how to improve the correlation coefficients, i.e., the signal to noise ratio for our measurements. Our approach is also the first step to link a behavior HDL simulator generated simulated power measurements to real power measurements.

Noise pollution due to road traffic is a major global concern because of its negative impact on the quality of life in communities everywhere. In Vietnam, traffic noise has become an increasingly noticeable and serious problem in large cities like Hanoi and Ho Chi Minh City. To gain more insight into the characteristics of this noise, intensive noise measurements were conducted in Hanoi and Ho Chi Minh City in September 2005 and September 2007, respectively. A comprehensive dataset of noise was obtained that included 24-h noise measurements as well as short-term noise recordings. The volume of traffic was also quantified by reproducing video camera recordings. Noise datasets from both cities were then compared with a dataset of Japanese traffic noise obtained in Kumamoto. The results showed that the traffic noise in Hanoi and Ho Chi Minh City was characterized by relatively high noise exposure levels due to the large number of motorbikes and frequent horn sounds. The sound of horns contributed a definite impact of 0-4 dB on noise exposure in Hanoi and Ho Chi Minh City, where noise levels decreased with the absence of horn sounds. Our results also showed differences in the characteristic traffic noise of Vietnam and Japan.

This paper presents a comparative analysis of three nonlinear filters for estimation of the location and velocity of a moving emitter, using time difference of arrival (TDOA) measurements received by two unmanned aerial vehicles (UAVs) as they traverse the surveillance region. The TDOA measurements are generated over time by comparing and subtracting leading edge time of arrivals (TOAs) of signals. The Cramér Rao lower bound (CRLB) of estimation errors is derived and used as the benchmark in performance analysis. The three nonlinear filters considered in the comparison are: a Gaussian mixture measurement integrated track splitting filter (GMM-ITSF), a multiple model filter with unscented Kalman filters (UKFs) and a multiple-model filter with extended Kalman filters (EKFs).

The benefits of Hyperion hyperspectral data to agriculture have been studied at sites in the Coleambally Irrigation Area of Australia. Hyperion can provide effective measures of agricultural performance through the use of established spectral indexes if systematic and random noise is managed. The noise management strategy includes recognition of "bad" pixels, reducing the effects of vertical striping, and compensation for

A two-channel multibit CA audio digital-to-analogconverter (DAC) with on-chip digital phase-locked loop and sample-rate converter is described. The circuit requires no oversampled synchronous clocks to operate and rejects input sample clock jitter above 16 Hz at 6 dB/octave. A second-order modulator with a multibit quantizer, switched-capacitor (SC) DAC, and single-ended second-order SC filter provides a measured out-ofband noise of -63 dBr with less than 0.1' phase nonlinearity.

A critical issue in image restoration is the problem of Gaussian noise removal while keeping the integrity of relevant image information. Clinical magnetic resonance imaging (MRI) data is normally corrupted by Rician noise from the measurement process which reduces the accuracy and reliability of any automatic analysis. The quality of ultrasound (US) imaging is degraded by the presence of signal dependant noise known as speckle. It generally tends to reduce the resolution and contrast, thereby, to degrade the diagnostic accuracy of this modality. For this reasons, denoising methods are often applied to increase the: Signal-to-Noise Ratio (SNR) and improve image quality. This paper proposes a statistical filter, which is a modified version of Hybrid Median filter for noise reduction, which computes the median of the diagonal elements and the mean of the diagonal, horizontal and vertical elements in a moving window and finally the median value of the two values will be the new pixel value. The results show that our proposed method outperforms the classical implementation of the Mean, Median and Hybrid Median filter in terms of denoising quality. Comparison with well established methods, such as Total Variation, Wavelet and Wiener filters show that the proposed filter produces better denoising results, preserving the main structures and details.

For testing the integration of the remote sensing related technologies into the water quality monitoring programs of Lake Garda (the largest Italian lake), the spatial and spectral resolutions of Hyperion and the capability of physics-based approaches were considered highly suitable. Hyperion data were acquired on 22nd July 2003 and water quality was assessed (i) defining a bio-optical model, (ii) converting the Hyperion atsensor radiances into subsurface irradiance reflectances, and (iii) adopting a bio-optical model inversion technique. The bio-optical model was parameterised using specific inherent optical properties of the lake and light field variables derived from a radiative transfer numerical model. A MODTRAN-based atmospheric correction code, complemented with an air/water interface correction was used to convert Hyperion at-sensor radiances into subsurface irradiance reflectance values. These reflectance values were comparable to in situ reflectance spectra measured during the Hyperion overpass, except at longer wavelengths (beyond 700 nm), where reflectance values were contaminated by severe atmospheric adjacency effects. Chlorophyll-a and tripton concentrations were retrieved by inverting two Hyperion bands selected using a sensitivity analysis applied to the bio-optical model. The sensitivity analysis indicated that the assessment of coloured dissolved organic matter was not achievable in this study due to the limited coloured dissolved organic matter concentration range of the lake, resulting in reflectance differences below the environmental measurement noise of Hyperion. The chlorophyll-a and tripton image-products were compared to in situ data collected during the Hyperion overpass, both by traditional sampling techniques (8 points) and by continuous flow-through systems (32 km). For chlorophyll-a the correlation coefficient between in situ point stations and Hyperion-inferred concentrations was 0.77 (data range from 1.30 to 2.16 mg m − 3 ). The Hyperion-derived chlorophyll-a concentrations also match most of the flow-through transect data. For tripton, the validation was constrained by variable re-suspension phenomena. The correlation coefficient between in situ point stations and Hyperion-derived concentrations increased from 0.48 to 0.75 (data range from 0.95 to 2.13 g m − 3 ) if the sampling data from the re-suspension zone was avoided. The comparison of Hyperionderived tripton concentrations and flow-through transect data exhibited a similar mismatch. The results of this research suggest further studies to address compatibilities of validation methods for water body features with a high rate of change, and to reduce the contamination by atmospheric adjacency effects on Hyperion data at longer wavelengths in Alpine environment. The transferability of the presented method to other sensors and the ability to assess water quality independent from in situ water quality data, suggest that management relevant applications for Lake Garda (and other subalpine lakes) could be supported by remote sensing.

Speech-in-noise measures are gaining relevance as audiologists understand the advantages of using outcome measures that demonstrate the need for and benefit from amplification. Two such speechin-noise measures are the Hearing in Noise Test (HINT) and the Quick Speech-In-Noise (Quick SIN) test. This study was conducted to determine how HINT and Quick SIN performance among young adults with normal hearing (N=15) compared to normative values, as well as to reach conclusions about the clinical utility of both tests. Results showed that Quick SIN measures and normative values were not statistically significantly different while the HINT measures and normative values were. The Quick SIN was found to have some advantages over the CD version of the HINT in terms of clinical use.

This review provides a comprehensive survey of noise research in MEMS. Some background on noise and on MEMS is provided. We review noise production mechanisms, and highlight work on the theory and modeling of noise in MEMS. Then noise measurements in the specific types of MEMS are reviewed. Inertial MEMS (accelerometers and angular rate sensors), pressure and acoustic sensors, optical MEMS, RF MEMS, surface acoustic wave devices, flow sensors, and chemical and biological MEMS, as well as data storage devices and magnetic MEMS, are reviewed. We indicate opportunities for additional experimental and computational research on noise in MEMS.

This paper describes a low power and element-scalable 60 GHz 4-element phased array transceiver implemented in a standard 65 nm CMOS process. Using a 1.2 V supply, the array consumes 34 mW/element including LO synthesis and distribution. Energy and area efficiency are achieved by utilizing a baseband phase shifting architecture, holistic impedance optimization, and lumped-element based design. Each receiver (RX) element provides 24 dB of gain with an average noise figure (NF) of 6.8 dB while the total saturated output power of the transmitter (TX) is 4.5 dBm. The array achieves 360 of phase shifting range with a worst-case measured phase resolution of 6 bits (TX)/ 5 bits (RX) while maintaining amplitude variations less than 0.5 dB.